スカイロジック List of Products and Services

In recent years, system security manufacturers have been increasingly expanding and are also engaged in the production of hardware products. This involves inspecting the presence or absence of bit inserts in covers that encase the equipment. 【Inspection Settings and Results】 By using the "Color Comparison Inspection" feature of EasyInspector, we were able to detect the differences in the presence or absence of bit inserts in four holes and determine visually similar counterfeit products (different items) in just 0.25 seconds. Our inspection software may also be of assistance on your production line. We look forward to your inquiries. 【Software and Equipment Used】 Software Used: EasyInspector710 Field of View: 367 x 292 mm Minimum Size of Inspection Target: 10 mm Number of Inspection Points: 4 Camera Resolution: 1.3 Megapixels Lens Focal Length: 6 mm Distance from Lens to Product: 330 mm Lighting: Ring Lighting Distance from Lighting to Inspection Item: Approximately 280 mm Current inspections can be performed with the 'EasyInspector2' color package [Color Comparison Extraction + Particle Count].

• Image Processing Software

We received an inquiry from a thermosensor manufacturing company regarding the automation of shape verification. This is a free evaluation based on the images you provided. Due to the spread of the COVID-19 virus, products that detect temperature are increasing in variety. We encounter new forms of the latest surface temperature detection systems in various locations. This free evaluation is from 2017, but it reaffirms that our inspection software is being utilized in various scenarios. 【Inspection Settings and Results】 By using the "Comparison with Master Image" feature of EasyInspector, we were able to determine visually similar items (different products) in less than 0.48 seconds. In actual inspections, the appearance may change due to factors such as lighting reflections, which could affect the inspection results. For inspection items labeled "unprocessed" or "punctured," the shapes differ, so inspection methods using backlighting may be required. Additionally, in the inspection of "sagging," the size of the sagging may affect the inspection results.

• Image Processing Software

A customer from a metal processing manufacturer inquired about using inspection software to prevent contamination due to product similarities, differences in plate thickness, and variations in hole diameter. 【Inspection Settings and Results】 By using EasyInspector's "Comparison with Master Image" function and "Color Comparison Inspection" function, we were able to detect the presence or absence and positional differences in four locations, allowing us to determine visually similar products (different items) in 0.25 seconds each. Since it was not possible to capture all inspection areas in a single field of view, we proposed using three cameras. 【Software and Equipment Used】 Software Used: EasyInspector300 Field of View: Approximately 198 x 147mm Minimum Size of Inspection Target: 10mm Number of Inspection Points: 4 Camera Resolution: 1.3 Megapixels Lens Focal Length: 12mm Distance from Lens to Product: 500mm Lighting: Indoor Fluorescent Light The current 'EasyInspector2' color package can perform inspections using the [Comparison with Master Image] and [Color Comparison Extraction + Particle Count] functions.

• Image Processing Software

This is a request for a free evaluation of cast products. There was an inquiry about wanting to incorporate inspections if they can be done at a low cost. There are still many inquiries about die-cast and cast products; nowadays, we often suggest easy settings using the AI-based inspection software DeepSky. If you are inspecting workpieces made of reflective materials like cast products while flowing them on a conveyor, please check "DeepSky." 【Inspection Settings and Results】 By using the "Scratch Inspection" feature of EasyInspector, we were able to detect the presence or absence of defects at one location (simultaneous inspection of three workpieces) and determine visually similar items (different products) in 0.3 seconds. The green numbers indicate OK (good products) within the acceptable range, while the red text indicates NG (defective). The settings for good and defective products can be changed.

• Image Processing Software

To ensure stable quality during shipment, many of our customers operate at low cost using our inspection software. 【Inspection Settings and Results】 By using the "Comparison with Master Image" feature of EasyInspector, we detected differences in two areas: "unwelded" and "punctured." Additionally, using the "Scratch and Defect Inspection" feature, we identified the black, band-like charred areas that occurred during "sagging." The inspection cycle time was 0.25 seconds. 【Software and Equipment Used】 Software Used: EasyInspector310 Field of View: Approximately 13 x 10mm Minimum Size of Inspection Target: 1mm Number of Inspection Points: 3 Camera Resolution: 1.3 Megapixels Lens Focal Length: 35mm + 10mm Macro Ring Distance Between Lens and Product: 130mm Lighting: Indoor Fluorescent Light The current 'EasyInspector2' color package allows inspection with the features of [Comparison with Master Image] and [Scratch and Defect Detection].

• Image Processing Software

We received an inquiry from the engine valve manufacturer through our website. They were using a conventional inspection software but were troubled by excessive false detections. Our company provides verification and support from technical staff on a daily basis. If you have any issues, questions, or uncertainties during operation, please feel free to contact us at any time. 【Inspection Settings and Results】 We conducted the inspection using a software called DeepSky, which utilizes AI (Deep Learning). By training the software on the areas we wanted to detect, it adjusts its own setting parameters and learns to recognize them. In this instance, it was able to determine water droplets and scratches. The image shows a successful assessment of a scratch. Our company is located in Hamamatsu City, Shizuoka Prefecture, and we serve numerous industrial machinery manufacturers and users, primarily in the automotive industry. We develop inspection software that is easy to integrate and sell outright, and we have received many repeat orders. 【Software Used】 Software Used: DeepSky

• Image Processing Software

We reported on the re-evaluation conducted with DeepSky, which was just released in 2020, using the sample images that you previously inquired about from the comprehensive manufacturer of containers and packaging materials. The inspection was performed using software that employs AI (Deep Learning). By training the software on the areas we want to detect, it can adjust its own setting parameters and recognize them. In actual operations, various patterns of defects (size and characteristics) are expected, so it is necessary to increase the number of training images. [Inspection Settings and Results] "DeepSky" significantly differs from conventional software and detection methods, allowing for the detection of pre-trained feature areas from the screen. I thought that "DeepSky" could be utilized for the inspection of coating amounts of the coating agent that you previously inquired about. Unlike before, it is no longer necessary to increase the number of inspection frames for certain settings. However, it is necessary to prepare multiple images in advance for cases of failure, but since September 2021, it has become possible to augment training images. The function to augment a single defective image into up to 36 images by adjusting brightness, orientation, angle, and noise has been implemented, making it more convenient to use.

• Image Processing Software

This is a request for a simple verification from a manufacturer of custom automatic machines, who specializes in high precision and high-speed transport. In the free sample evaluation, we will first conduct a simple verification using the samples or images provided, and report the verification results. After that, we recommend conducting tests (feasibility verification) assuming actual operation, where we will evaluate processing time and judgment accuracy. 【Inspection Settings and Results】 We conducted verification using the "Dimension and Angle Inspection" function of EasyInspector on the samples we received. We measured the vertical dimension of the clip and made pass/fail judgments based on the overall length. It was possible to make pass/fail judgments in 0.89 seconds. The inspection cycle may vary depending on the specifications of the PC. 【Software Used】 Software used: EasyInspector710 The current 'EasyInspector2' MS (MeaSure) package can perform inspections for [Position and Width Measurement] and [Angle Measurement].

• Image Processing Software

We have received many inquiries from industrial equipment manufacturers regarding various case studies. This time, we attempted to set up a test to determine the presence or absence of plastic parts (balls). The cases introduced on this site are for simple verification. We prepare lighting, cameras, lenses, etc., to test whether we can detect the defects we want to see. Typically, we request about two types of samples and detection targets. Since simple verification is a task to confirm the feasibility of detection, quantitative evaluations such as detection accuracy using a large number of samples and the correlation between image resolution and detection accuracy are generally not included. [Inspection Setup and Results] We conducted an inspection of the presence or absence of parts (balls) using the samples you provided. By using ring lighting to make the balls appear black, we were able to determine the presence or absence of the five parts in 0.14 seconds using EasyInspector's "specified color presence check" function.

• Image Processing Software

This is an inquiry from a customer who wishes to quantify the texture of fiber-reinforced resin molded products. The preliminary verification is based on the images provided. For accurate verification, sending samples that can also provide guidance on the imaging environment is the most reliable way to ensure stable reporting. However, there are also many requests to send images via email. After determining the pass/fail status through simple inspection, we will proceed with verification while considering the operational methods. 【Inspection Settings and Results】 By using the "Presence of Specified Color Inspection" feature of EasyInspector, we conducted an overall inspection with inspection frames, allowing for quantification. There were patterns resembling cuts, and we determined that EasyInspector provides more stable inspection than DeepSky. 【Software Used】 Software used: EasyInspector710 The current 'EasyInspector2' color package can perform inspections for the "Presence of Specified Color."

• Image Processing Software

We often receive requests to count the number of necessary parts while inspecting for any defective items in inquiries to our company. Unmanned inspection and counting on a conveyor belt is a field in which DeepSky excels. This time, we received an inquiry about whether we could count processed parts (e.g., φ0.8×2.5mm) arranged randomly on a flat pallet. They provided images using backlight illumination. 【Inspection Settings and Results】 The left image shows a part of the work screen for the annotation process, where we outline the areas we want to identify (defects). As can be seen in the right image, all 10 annotated teacher images used were counted correctly. The ratio of successful counts for non-teacher images was 30%. There was a tendency for higher rates of miscounting with parts that were more closely stuck together. By using non-detected images for further training, we can detect defects that were previously undetectable. Further training is also one of DeepSky's strengths.

• Image Processing Software

In an electronic component manufacturer, if the terminals do not function properly, the product cannot be established. Issues such as incorrect wiring combinations or deformation of the terminals can be cited as problems. This time, we received an inquiry to inspect whether the terminals are deformed using image processing. 【Inspection Settings and Results】 Using the "Color Comparison Inspection" function of EasyInspector's "Comparison with Master Image," we set inspection frames on four terminal areas to detect differences from the good product master image. The pass/fail criteria were established based on the minimum value when inspecting defective products, allowing us to determine pass or fail. 【Inspection Settings and Results】 Software Used: EasyInspector310 Number of Inspection Points: 4 Camera Resolution: 1.3 million pixels Lens Focal Length: 50mm Distance Between Lens and Product: Approximately 210mm Lighting: Thin Ring Lighting The current 'EasyInspector2' color package can perform inspections using the "Comparison with Master Image."

• Image Processing Software

If there are chips on the substrate, they are treated as defective products. Electronic component manufacturers pay close attention to the handling of parts, but inevitably, a few defective items do occur. The defect in this case was a chip on the side of the substrate. During visual inspection, it was difficult to distinguish between the chipped area and the substrate pattern, making the inspection challenging. The goal was to supplement this difficulty with image recognition to inspect efficiently and accurately. 【Inspection Settings and Results】 Using the "Scratch Inspection" feature of EasyInspector, we inspected the chips on the side of the substrate. By tilting the substrate slightly, the chips became easier to see. When we set the detection sensitivity (luminance difference) to a strict level (10), we were able to detect the chipped area, but the substrate pattern was also detected. After further inspection, we loosened the detection sensitivity (to 20), which successfully allowed us to detect only the chips without detecting the substrate pattern. 【Software and Equipment Used】 Software Used: EasyInspector310 Minimum Size of Inspection Target: Approximately 3-5mm Number of Inspection Points: 4 Camera Resolution: EI-Scan Current inspections can be performed with the 'EasyInspector2' color package [Scratch and Object Detection].

• Image Processing Software

The metal parts used by automobile manufacturers may sometimes be shipped with defects such as dents or black spots, but if the dimensions are incorrect, it is pointless. This led us to use our software to inspect those dimensions. 【Inspection Settings and Results】 Using the "Dimension Angle Inspection" feature of EasyInspector, we measured three different areas with varying lengths. First, to clearly define the edges, we used backlighting; however, when the inspection object was placed directly on the backlight, the light reflected irregularly, causing the edges to appear blurred. Therefore, we took the photos at a distance of about 40mm from the backlight, placing the object on a glass surface. Since the inspection object appeared dark, we detected the bright and dark areas from top to bottom to measure the dimensions.

• Image Processing Software

The OCR reading printed on the chip capacitors of electronic component mounting boards is a feature of our inspection software that many companies utilize. Additionally, it is often capable of detecting damage to components, solder debris, and the presence of dirt. 【Inspection Settings and Results】 By using the "OCR" function of EasyInspector, there were parts of the IC chip's serial number that could be read by OCR and parts that could not. This verification was conducted in 2015, and it has since been upgraded to the "PCRPro" function, allowing for more accurate readings. As shown in the left image, readings can be performed by registering a dictionary and setting binarization, but it can be challenging if the characters are connected, lines are interrupted, or they appear as dots. Please try our EasyInspector to see how well it can perform binarization. 【Software Used】 Software Used: EasyInspector710 Field of View: No records Number of Inspection Points: 3 The current 'EasyInspector2' RD (ReaDing) package can inspect using 【OCR (Character Recognition)】【Machine Learning OCR】.

• Image Processing Software

We received an inquiry from a camera control equipment manufacturer regarding the customer's request to create a system for air conditioning implementation inspection. 【Inspection Settings and Results】 By using the "Comparison with Master Image and Presence of Specified Color Inspection" feature of EasyInspector, we were able to detect the presence and positional differences in three locations and make a judgment in 0.34 seconds. For each of the three inspection locations, we propose two types of inspection methods: "Comparison with Master Image" and "Presence of Specified Color Inspection." The inspection is conducted using the images provided. 【Software Used】 Software Used: EasyInspector710 Number of Inspection Locations: 3 The current 'EasyInspector2' color package can perform inspections with [Presence of Specified Color] and [Comparison with Master Image].

• Image Processing Software

The inspection of solder bridges, whether present or absent, is one of the defects we receive numerous inquiries about. Verification is conducted by sending photos. Our affordable inspection software is being utilized across various sectors. We hope to support your company in stable product manufacturing with our inspection software. 【Inspection Settings and Results】 By using the "Luminance Change Inspection" feature of EasyInspector, we were able to determine a solder bridge at one connected solder point in 0.04 seconds. The pink frame in the right image represents the inspection area. The green line in the left image indicates luminance. The pass or fail is determined by how many low luminance areas (black parts) between the solders are detected, and the settings ensure that the solder bridge does not form a clean green wavy line, resulting in a failure. In this case, a count of 6 was measured, which is a pass. Additionally, we were able to simultaneously assess the presence or absence of other components such as chips and capacitors, as well as their polarity, for a total of 10 inspection points. 【Software Used】 Software Used: EasyInspector710 Number of Inspection Points: 10

• Image Processing Software

We received an inquiry regarding the optical character recognition of serial numbers on laser diodes from an electronic component manufacturer. Our inspection software, EasyInspector, enhances processing speed by converting characters into two colors, black and white, to clearly define the boundary between the inspection target and the background (binarization). By using the "OCR Pro" feature of EasyInspector, we were able to detect the presence and positional differences of three holes, allowing us to determine visually similar counterfeit products (different items) in 0.05 seconds. This evaluation was based on the images provided. The image on the right shows the display when inspection results are recorded in a CSV file. In this way, all inspection results can be recorded, and it is also possible to keep a visual record.

• Image Processing Software

It is common in any industry to manufacture seemingly similar products on a single line. Even in audio equipment manufacturing, there have been incidents where the rear display of Blu-ray recorders of the same shape was mistakenly swapped, or defects occurred where the printing was smudged and unreadable. 【Inspection Settings and Results】 By using EasyInspector's "Comparison with Master Image" function, we were able to detect six printing discrepancies and determine visually similar counterfeit products (different items) in 0.36 seconds. Since a printing deviation of approximately ±1mm is considered acceptable, it would be deemed unacceptable under the current inspection settings, necessitating some adjustments. For example, one could set the verification level to a larger value or set the deviation correction for each inspection frame to "automatic" to perform corrections at various points, while conducting separate dimensional angle inspections for positional deviations. 【Software and Equipment Used】 Software Used: EasyInspector310 Field of View: Approximately 200 x 130mm Minimum Size of Inspection Target: 2mm Number of Inspection Points: 6 Camera Resolution: 3 million pixels Lens Focal Length: 12mm Distance from Lens to Product: 280mm Lighting: Indoor fluorescent lights

• Image Processing Software

The ferrule made from polyphenylene sulfide (PPS), a thermoplastic resin, is a connector that allows for the high-precision, high-density mass connection of multi-core optical fibers. However, a resolution of 0.01μm in image processing is essential, making it a very challenging situation, and there was a request for hole pitch measurement of the MT ferrule. Additionally, there were multiple inquiries regarding character recognition of semiconductor laser chips and measurement of the amount of adhesive droplets. 【Inspection Settings and Results】 For character recognition of semiconductor laser chips, by using the "OCR Pro" function of EasyInspector, it was possible to read numbers at one location (15 characters) and make a judgment in 0.2 seconds. 【Software Used】 Software Used: EasyInspector Number of Inspection Locations: 1 (15 characters)

• Image Processing Software

It seems that among the customers using EasyInspector, the majority are manufacturers who use it for inspecting electronic circuit boards. This time, we are also dealing with the assembly of electronic circuit boards. Due to requests to inspect various parts, we received inquiries about camera environments and settings after downloading the free trial version from our website. 【Inspection Settings and Results】 By using EasyInspector's "Color Comparison Inspection" feature, we were able to detect differences in one location and determine visually similar items (different products) in less than one second. Our website offers a service where you can use EasyInspector's "60-day free trial version" from the download page. There has been an increasing trend in inquiries regarding the inability to lose work due to security and compliance concerns, but many customers are making use of it.

• Image Processing Software

Our inspection software users include manufacturers of precision motors. They focus on precision casting, emphasizing technology and experience. We are pleased that our inspection software can contribute to such high-performance, precise manufacturing. [Inspection Settings and Results] Settings were made with DeepSky. When illuminated, the area closest to the camera in the center glows white; this is registered as OK, and when OK is detected, it is considered a pass. Even in areas where OK cannot be detected, if NG is not detected, it is set to pass, allowing us to meet the customer's judgment requirements. The image shows the types of labels (for distinguishing the parts to be detected). [Software and Equipment Used] Software Used: DeepSky 2.0 Field of View: Approximately 48 x 36 mm Minimum Size of Inspection Target: 20 mm Number of Inspection Points: 1 (Label 4) Camera Resolution: 1.3 million pixels Lens Focal Length: 12 mm Distance Between Lens and Product: 130 mm Lighting: Ring Lighting Distance Between Lighting and Product: 130 mm

• Image Processing Software

Deformation of the insertion port in cassette gas products can lead to significant accidents. We hope that our inspection software will be useful for your safety. In this free evaluation, we used the software DeepSky, which employs AI (Deep Learning) for inspection. By training the software on the areas we want to detect, it adjusts its own setting parameters and learns to recognize them. [Inspection Settings and Results] By using DeepSky's inspection capabilities, we determined multiple types of defects. We assessed the presence or absence of each type of defect based on scratches, shadows, and reflections, achieving a judgment time of 0.33 seconds. The labels were divided into three categories: scratches, shadows, and reflections, and we set up the software to learn the specific defects we wanted to identify. The method of specifying these defects and how to capture the images is crucial for image inspection.

• Image Processing Software

Manufacturers of monitoring and measurement devices are considering our inspection software. We conducted a free evaluation for detecting scratches on the device's hardware. Sending actual samples allows us to provide the most reliable report. In that case, you will need to send both good products and the workpieces with defects you want to detect. Please contact us for more details. 【Inspection Settings and Results】 The process of enclosing the areas to be detected in a rectangle, as shown in the left image, is called annotation. Since the scratches were of different types, we labeled and registered them as "Scratch A / Scratch B / Scratch C." Although it was not part of the requested inspection items, we were able to capture a small dent on the cylindrical part clearly, so it was included as a detection target (Scratch C). (Detection will not occur unless annotated.) The clip was fixed, so the clip area was set outside the field of view. 【Software and Equipment Used】 Software Used: DeepSky Learning Edition Field of View: Approximately 64 x 51 mm Minimum Size of Inspection Target: 20 mm Number of Inspection Points: 1 in total Camera Resolution: 1.3 million pixels Lens Focal Length: 25 mm Distance Between Lens and Product: Approximately 260 mm Lighting: Ring Lighting

• Image Processing Software

"Marks from screws" is a very common request for verification. While it may be better to inspect using our conventional general-purpose image inspection software "EasyInspector," in operations where judgments are made on a conveyor or during work, we sometimes recommend using the AI-based inspection software "DeepSky" for defects like marks that come in various colors and shapes. This time, we created a thread conveyor and reported on the detection of defects around the screws in a full 360-degree rotation. [Inspection Settings and Results] The task of enclosing the area we want to detect (in this case, marks) in a rectangle is called annotation. We trained the model with 24 annotated teacher images, rotating them approximately 2300 steps (about 15 minutes). The training time varies depending on the specifications of the PC. In the right image, the marked area is indicated by a green detection frame.

• Image Processing Software

Even manufacturers who specialize in precision cutting and grinding processes are utilizing our inspection software for high-quality precision machining technology and quality management systems. 【Inspection Settings and Results】 As a result of verification using the samples provided, it was possible to detect scratches on the screws. The inspection was conducted using a software called DeepSky, which employs AI (Deep Learning). By training the software to recognize the desired scratches, it adjusts its own setting parameters to identify them. Five samples were photographed from different angles and the opposite side, resulting in 22 training images, with the left image set as the reference. The right image shows the detection frame. 【Software and Equipment Used】 Software Used: DeepSky Field of View: 30 x 25mm Minimum Size of Inspection Target: 0.2mm Number of Inspection Points: 1 overall Camera Resolution: 1.3 million pixels Lens Focal Length: 35mm + 5mm close-up ring Distance Between Lens and Product: Approximately 160mm Lighting: Indoor fluorescent lights

• Image Processing Software

In the metal product manufacturing industry, deformation caused by spatter has been a challenge for some time. Recently, there was an incident where defective products were generated due to spatter occurring on the contact surface, leading to inquiries through a trading company. This customer has been using our inspection software for some time. 【Inspection Settings and Results】 We were able to detect the issues using software called DeepSky, which utilizes AI. DeepSky excels at inspections that involve searching for defects throughout the entire screen. The image on the left is a teacher image that trains the AI on the defective areas, while the right side shows the detected image, with the numbers indicating the AI's confidence level in percentage (number of recognition points). Since the spatter defects were very small and it was difficult to inspect the entire workpiece with a single camera, we are proposing inspections using multiple cameras. 【Software and Equipment Used】 Software Used: DeepSky Field of View: 70 x 60 mm Minimum Size of Inspection Target: 1 mm Number of Inspection Points: 1 overall Camera Resolution: 1.3 million pixels Lens Focal Length: 6 mm Distance between Lens and Product: Approximately 110 mm Lighting: Ring lighting Distance from Lighting to Inspection Item: Approximately 300 mm from above

• Image Processing Software

Metal welded parts, such as automotive components, often have defects like bead misalignment, blowholes, and tears due to specification differences, which have been common inquiries for a long time. Previously, inspections were conducted using EasyInspector with fixed positioning, but with the inspection capabilities of DeepSky released in 2020, it has become easy to set up inspections without fixed positioning. 【Inspection Settings and Results】 The target areas to be detected were enclosed in frames and labeled by type. A total of 14 images were used as training data, consisting of 8 OK images and 6 NG images. The learning process was executed for 2,000 steps, and the graph converged in about 16 minutes. The time may vary depending on the specifications of the PC used. In this inspection, since we are detecting the defective areas that were trained, it was set so that if even one defect is detected, it would be considered NG (only OK when the count is from 0 to 0), allowing for the detection of welding defects.

• Image Processing Software

In the manufacturing of metal press products such as automotive parts, there is often a process for attaching eyelets. This time, we will conduct inspections for the presence or absence of eyelets and rubber parts. We received good products and defective products that do not have all the parts attached. 【Inspection Settings and Results】 Using DeepSky's inspection function, we were able to classify good products and defective products without all the parts as negative by using them as teachers and marking random positions where eyelets are missing. It is set to pass only when the correct quantity of eyelets (and rubber parts) is detected. If even one eyelet is missing, it will be marked as negative due to quantity mismatch. If you want to check "which eyelet is missing," it is possible to use the area specification function, but for now, we conducted the inspection with settings to determine only OK or NG. The left image shows the work of enclosing the parts we want to teach, called "annotation." The right image is the detection frame image, where the numbers represent the AI's confidence level percentage, referred to as "recognition points."

• Image Processing Software

We will verify whether we can detect "dents on the ball," "dents on the tapered section," and "indentations on the tapered section" based on a request from an industrial equipment manufacturer. By creating a striped pattern on the reflective part of the ball, it becomes easier to identify the dented areas due to the resulting step difference. 【Inspection Settings and Results】 We inspected 25 images, including 10 images of "dents on the ball," 5 images of "dents on the tapered section," 5 images of "indentations on the tapered section," and 5 images of "good products." Out of the 25 images, 22 were correctly identified as either good products or defective parts. The three images of "dents on the tapered section" could not be recognized as defective parts; however, considering that in actual operation, multiple shots (around 3 times) are expected to be taken during one full rotation, it does not necessarily mean that the defective parts that were not recognized in the verification will always go unrecognized.

• Image Processing Software

This is a verification to distinguish the defects of "scratches," "bleeding," and "spots" on metal painted products at the request of an industrial machinery manufacturer. We decided to photograph and verify by changing the orientation and position of a single defective sample. 【Inspection Settings and Results】 This time, we were able to make judgments by creatively adjusting the lighting during photography. Due to the size of the coaxial illumination we own, we could not capture the entire workpiece, so we focused on the damaged areas for imaging. Normally, inspections are conducted by capturing a field of view approximately 1.5 times the size with appropriately sized coaxial illumination, but we believe that the detection accuracy will be equivalent to that of this case based on the size of the damaged areas. To improve detection accuracy, we can use photos of misjudgments as training images for further learning. The left image is the "annotation" used to set parameters by enclosing the defective areas we want to detect. The right image is the "frame" detecting defects after learning and parameter setting.

• Image Processing Software

It seems that manufacturers are struggling with various defect detections for saw blades, just like with other metal products, including issues such as unprocessed areas, dents, compression marks, chips, and foreign objects. For image inspection of shiny metal workpieces, please contact our company. This time, we are detecting wear on saw blades based on a verification request from a trading company we have been dealing with for some time. 【Inspection Settings and Results】 The judgment was made based on the NG images provided. Although we were unable to make sufficient settings due to difficulties in comparing with good products, we were still able to make some judgments, though some were misjudged. We report this as one result. The images show the defective areas that were successfully detected, highlighted with a light blue frame. The numbers indicate the confidence percentage (number of recognition points) from the inspection software. 【Software Used】 Software used: DeepSky Learning Edition Number of inspection points: 1 location (finding the worn area from the entire screen)

• Image Processing Software

We received a request for inspection of cast precision parts from a manufacturer of production equipment design and fabrication. "Porosity" has been a frequently inquired case for some time. With DeepSky, released in 2020, it is easy to set up, does not require fixed positioning, can detect various defects with unstable shapes, and is also skilled at detecting defects in glossy workpieces. We have reported numerous evaluations of "porosity" inspections. [Inspection Setup and Results] This time, since the size of the defects was small, we narrowed the field of view to about 50mm, and DeepSky was able to recognize it well. Even if the patterns of defects to be detected increase, it seems likely that detection can still be achieved as long as the field of view is set appropriately. Our inspection software is also helpful for detecting fine defects in precision parts. [Software Used] Software Used: DeepSky Learning Edition Field of View: 50 x 40mm Minimum Size of Inspection Target: 0.5mm Number of Inspection Points: 1 (finding porosity from the entire screen)

• Image Processing Software

This is an inquiry from a manufacturer engaged in a wide variety of businesses, including iron gear processing, processing of irregular iron products, aluminum casting, aluminum processing, and assembly. I believe that many manufacturers, not just the customer in this inquiry, are still struggling with issues such as unprocessed materials, dents, pressure casting, and the detection of casting defects in aluminum cast products. Even if it is a work that was previously given up on, we welcome inquiries to our company. 【Inspection Settings and Results】 Using a software called DeepSky, which employs AI (Deep Learning), we were able to detect foreign objects in metal products. This software was released in 2020. By training the software on the areas we want to detect, it adjusts its own setting parameters and learns to recognize them. The image shows the detection frame, and the numbers indicate the AI's confidence level percentage and the "number of recognition points." 【Software Used】 Software used: DeepSky Learning Version Number of inspection points: 1 (to find foreign objects from the entire screen)

• Image Processing Software

We received a request for evaluation from a manufacturer of production equipment. This pertains to the judgment of defects caused by metal chips adhering to the workpiece. The DeepSky system released in 2020 is known for its ease of setup, the elimination of the need for fixed positioning, its ability to detect various shapes of defects, and its proficiency in detecting defects in shiny metal products, leading to numerous evaluations of metal product inspections. 【Inspection Setup and Results】 To determine the "metal chips inside the workpiece's hole," we made adjustments to the lighting. We attempted an inspection that captures images inside the hole, and this time, the bottom of the hole was clearly visible, allowing for accurate judgment. The initial evaluation is a report on whether simple detection is possible; however, depending on the position and shape of the defects, there may be instances where detection is challenging. After our free evaluation, we would like customers to directly experience the accuracy and setup methods before implementation, so we kindly ask you to utilize our free demo unit lending service. 【Software Used】 Software Used: DeepSky Learning Edition Minimum Size of Inspection Target: 2mm Number of Inspection Points: 1 (finding defects from the entire screen) Lighting: Coaxial Illumination

• Image Processing Software

We received an inspection request from a manufacturer of production equipment. The inspection is for determining the chipping of a metal product, specifically a "gear." They sent us images of 20 defective items and 5 acceptable items. For some workpieces that are difficult to send as samples, verification can sometimes be done through photographs. 【Inspection Settings and Results】 Using DeepSky's inspection function, we were able to accurately determine the chipping of the metal workpiece (gear). The process of setting up the areas to be detected by enclosing them in rectangles is called annotation; in this case, we only enclosed the defective parts for training. The images show the detection frames. The numbers indicate the AI's confidence level percentage (number of recognition points). If the number of recognition points is low or if there are misjudgments, further training can be conducted. DeepSky, released in 2020, is easy to set up, does not require fixed positioning, can detect various types of defects in shapes, and is particularly good at detecting defects in shiny workpieces like metal products. We have reported numerous evaluations of metal product inspections. 【Software Used】 Software Used: DeepSky Learning Version Number of Inspection Points: 1 (detecting defects from the entire screen)

• Image Processing Software

We received an inquiry about the inspection of fine precision machinery from a manufacturer engaged in the design of industrial machinery and the development of software. If sending sample products is difficult, it is also possible to verify using photographs. They were considering whether it could be automated to determine the sorting of good and defective products, which is currently done through visual inspection. 【Inspection Settings and Results】 It was possible to determine burrs and black spots on metal products. The report was based on a configuration using two cameras, each assumed to use a 0.5x macro lens and a 35mm prime lens. Even with verification through sent images, we are providing support as much as possible by listening to the details and suggesting imaging environments such as cameras. 【Software Used】 Software Used: DeepSky Learning Version Number of Inspection Points: One location across the entire screen (to find burrs and black spots)

• Image Processing Software

The NumberVision API is an API specialized in reading performance. It instantly recognizes vehicle license plates from captured images and digitizes the data using AI technology. It supports license plate recognition in various scenarios, making it easy for software and web service developers to incorporate. 【Features】 ■ Recognition rate of 99.9%! It can read from anywhere within the image. Furthermore, with multi-plate reading, it can simultaneously read multiple license plates from a single image. ■ It is now possible to recognize license plates in dark places such as dimly lit areas, dusk, and nighttime, which were previously considered difficult. This allows for operation in various situations, including locations with vehicle entry and exit other than parking lots, both outdoors and indoors. ■ No initial costs! If you don't use it in a month, it costs nothing! It has an affordable and user-friendly pricing structure, allowing you to use only what you need when you need it. You can experience license plate recognition from the NumberVision API product page of Skylogiq! Please give it a try. https://skylogiq.co.jp/index.php/products/numbervisionapi/

• Other image-related equipment

Even with the same material and similar shapes, there are many cases where texture can be perceived and judged. We also sell to trading companies and industrial equipment manufacturers. Please feel free to contact us. 【Inspection Settings and Results】 It was possible to determine the presence or absence of processing (front or back) of the nuts through image processing using deep learning. Since there is almost no difference in the images between those that had chips removed and those that did not, they were treated as the same for inspection purposes, and a total of 20 pieces, 10 processed and 10 unprocessed, were used as training data, resulting in good judgment. Deep learning is one of the machine learning methods that teaches computers to learn the thinking processes that humans naturally perform. Our inspection software, DeepSky, is designed with this AI technology. 【Software Used】 Software Used: DeepSky Learning Version Number of Inspection Points: 1 (Determining whether the workpiece is front or back)

• Image Processing Software

We received inquiries regarding multiple inspections, including unprocessed iron gear, pressure contact detection, burr residue on aluminum case parts, and confirmation of hole penetration in aluminum parts. Our company offers free evaluations that result in a simple "can do" or "cannot do" judgment. We can also accept paid testing. Please provide us with details about the specific operations. 【Inspection Settings and Results】 Continuous inspections are being conducted while manually rotating the workpiece slightly. Since the learning is not complete, there were some false detections, but the NG areas themselves were recognized. The ability to use the retraining function to improve the accuracy of inspection settings is one of the strengths of the software using AI (Deep Learning). 【Software Used】 Software used: DeepSky Learning Edition Number of inspection points: 1 (finding multiple defects from the entire screen)

• Image Processing Software

We will test the detection of scratches on metal sheets based on an inquiry from a copper manufacturer. This involves verification using provided photos. A copper sheet approximately 1mm thick is rolled up like toilet paper, and we are considering whether to inspect it while capturing images at low speed during the rolling process or to stop the line to take pictures and then inspect. In the first stage of a simple free evaluation, we were able to detect the scratched areas, but we are mistakenly detecting white areas on the image that are not scratches, making it difficult to distinguish. If we can improve the lighting to illuminate as wide an area as possible uniformly, inspection seems feasible. The images provided were used as "training data," and this is the result of the processing. Since these are training data images, we can make highly accurate judgments. The numbers represent the AI's confidence level percentage, referred to as "recognition points." [Software Used] Software: DeepSky Learning Version Number of inspection points: 1 across the entire screen

• Image Processing Software

We received a request for inspection of deformation of clips from a manufacturer specializing in renovations and remodeling. The inspection system was specifically envisioned as follows: drop each sample one by one due to vibration, move it to the camera section via a conveyor belt, determine and sort using the camera, and then the conveyor belt separates the acceptable products from the defective ones. **[Inspection Settings and Results]** We conducted inspections for shape defects using the samples we received. We verified using two patterns: from above and from the side, and it was possible to identify acceptable and defective products from above. The side inspection was able to detect the "angle of the edge," the "gap" in the clip section, and "twisting." The left image shows three types detected, while the right image displays the separated labels. There is no specified quantity for "OK," and the setting for defective is from 0 to 0 (if even one is present, it is considered NG). **[Software and Equipment Used]** Software used: DeepSky Learning Edition Field of view: Approximately 40 x 30 mm Minimum size of inspection target: 30 mm Number of inspection points: 3 Camera resolution: 1.3 million pixels Lens focal length: 25 mm Distance between lens and product: Approximately 170 mm Lighting: Indoor fluorescent lights

• Image Processing Software

This is an inquiry from a manufacturer of aluminum products and heat transfer processing with whom we have had a business relationship for some time. We will detect three types of defects: "something like dirt," "linear marks," and "dot-like marks." Sending actual samples will allow us to provide the most reliable report. In that case, we will need you to send several good products and workpieces with the defects you want to detect. Please contact us for more details. [Inspection Settings and Results] Since the scratches were of different types, we labeled them as "A / B / C" and registered them, making it possible to detect the scratches. The process of enclosing the areas we want to detect in a rectangle, as shown in the left image, is called annotation. We verified this using DeepSky, which can detect without fixed positioning, even at various orientations and angles during the work. DeepSky is software that excels in such inspections and is utilized across various industries.

• Image Processing Software

The label equipment manufacturer has also been packaging needles and inquired about automating the visual inspection to ensure they are properly packaged. We will provide a free evaluation to determine whether we can identify "duplicates," "tilts," and "vertical misalignments" of the products after packaging. 【Inspection Settings and Results】 After conducting training with the samples you sent, we were able to identify good products, duplicates, tilts, and vertical misalignments. For inspection, it is necessary to transport the sheet as parallel as possible to the camera angle. We have set the field of view to evaluate 10 items in a single shot and inspection. The left image shows the display indicating that "10 good products" have been detected within the screen. The right image shows that "9 good products and 1 duplicate" have been detected, resulting in a failure judgment. 【Software and Equipment Used】 Software Used: DeepSky Learning Version Field of View: Approximately 78 x 62 mm Minimum Size of Inspection Target: 2 mm Number of Inspection Points: 1 (Pass if there are 10 good products within the screen) Camera Resolution: 1.3 million pixels Lens Focal Length: 25 mm Distance Between Lens and Product: Approximately 485 mm Lighting: Indoor fluorescent lights

• Image Processing Software

This is an external inspection at a metal parts manufacturer that produces chip saws. Although the inquiry was about dimensional angle inspection, upon discussion, it became clear that the request was for the detection of chipping and scratches. 【Inspection Setup and Results】 For the time being, we verified larger chipping and scratches, and it seemed that they could be detected without any issues. If it is something that can be detected by DeepSky (our AI inspection software), we can automatically conduct continuous inspections as shown in the video, stopping and notifying when a defect is found. We also conducted a demonstration where the saw's rotation was manually operated, and an NG was issued when an abnormality entered the field of view. 【Software Used】 Software Used: DeepSky Number of Inspection Points: 1 location, entire screen

• Image Processing Software