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Visual inspection software Product List and Ranking from 19 Manufacturers, Suppliers and Companies | IPROS GMS

Last Updated: Aggregation Period:Feb 18, 2026~Mar 17, 2026
This ranking is based on the number of page views on our site.

Visual inspection software Manufacturer, Suppliers and Company Rankings

Last Updated: Aggregation Period:Feb 18, 2026~Mar 17, 2026
This ranking is based on the number of page views on our site.

  1. スカイロジック Shizuoka//software
  2. エーディーディー Kyoto//software
  3. 株式会社Roxy Aichi//IT/Telecommunications
  4. 4 藤川伝導機 Tokyo//Industrial Machinery
  5. 5 HACARUS Kyoto//others

Visual inspection software Product ranking

Last Updated: Aggregation Period:Feb 18, 2026~Mar 17, 2026
This ranking is based on the number of page views on our site.

  1. AI General Purpose Appearance Inspection Software 'EasyInspector2' スカイロジック
  2. [AI Image Inspection Case] Measurement of the Width of the Blade at the Center of the Drill スカイロジック
  3. AI visual inspection software "DeepSky" スカイロジック
  4. [AI Image Inspection Case] 7-Segment Display Reading スカイロジック
  5. 4 We will automate simple visual inspections such as forgetting to attach parts and the presence or absence of processing holes. エーディーディー

Visual inspection software Product List

391~420 item / All 466 items

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[AI Image Inspection Case] Implementation Inspection of Automotive Interior Parts

We will conduct implementation inspections of automotive interior parts using AI image inspection software!

Automotive parts and other resin-molded components may have variations in the presence or absence of holes and their positions due to differences in specifications. However, in the case of similar products, accidents have occurred where similar but different items were shipped because they looked almost identical. Our company is located in Hamamatsu City, Shizuoka Prefecture, an area with many automotive manufacturers, so we have the impression that most of our customers are in the automotive parts manufacturing industry. 【Inspection Settings and Results】 By using EasyInspector's "Color Comparison Inspection" feature, we were able to detect the presence or absence of holes, their positions, and color differences in 10 locations, and determine similar-looking items (different products) in less than 3.32 seconds. We were able to inspect 5 plastic pins (green), 2 plastic pins (white), 1 urethane tape, 1 metal pin, and 1 urethane resin in a single shot and inspection.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Contamination Dirt Inspection

We will detect contaminants of size 0.3 mm² within the resin molded products.

A resin molded product manufactured by an automotive manufacturer. We received an inquiry from our company with the aim of detecting 0.3 mm² size contaminants through image processing to improve work efficiency. 【Inspection Settings and Results】 Using the "Scratch and Flaw Inspection" function of EasyInspector, we set it up to detect 0.3 mm² size contaminants. The color of the flaws was set to black, and the detection was configured to identify darker colors compared to the surrounding pixels. The detection sensitivity was set to 3, as a lower number indicates better sensitivity; however, due to the small size of the target contaminants, even hair and dust were judged as foreign substances. As part of the operation, we proposed detecting contaminants and hair as NG (non-conforming) through image inspection, followed by a visual confirmation of the NG items.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Rubber Parts Assembly Inspection

We conduct visual inspections of resin-molded parts related to automobiles and determine the presence or absence of rubber part installation and detect any double installations.

There was a request to photograph products arranged on a pallet. You were looking for inspection software that could be generalized to other parts by exchanging the arranged pallets. 【Inspection Settings and Results】 By using EasyInspector's "Color Comparison Inspection and Presence of Specified Color Inspection" function, it was possible to determine in less than 0.57 seconds whether the rubber parts of 25 products arranged in the pallet during shipping packaging were correctly implemented.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Presence or Absence of Culture Chip

We will use AI image inspection software to count culture chips and determine the presence or absence of parts!

At the equipment cleaning company, counting the culture chips and confirming their presence or absence had become a hassle. You were considering image inspection to solve this issue and contacted our company. 【Inspection Setup and Results】 We conducted verification of pass/fail judgment based on the presence or absence of parts and counting using the samples you provided. By installing backlighting on the rear side, we were able to emphasize the target parts for imaging and detection. Since parts near the outer edge can appear differently at an angle, we used a 25mm lens to capture images from as high a position as possible (ensuring the entire tray is visible in the field of view). Using EasyInspector's "presence or absence of specified color" and "detection size judgment function," we counted the parts (rings) of the target size to determine pass/fail based on quantity.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Product Defects

We will conduct inspections of scratches that occur on the side walls of products using AI image inspection software!

The industrial equipment and machinery manufacturer you inquired about has requested multiple simple verifications in the past. This time, the contact is regarding consultation on inspection methods for scratches that occur on the side walls. However, detecting "scratches" is not a must for the ongoing inspection, and they are looking for technical cooperation on how the inspection can be conducted. 【Inspection Setup and Results】 By using the "Scratch Detection" feature of EasyInspector, we were able to determine a scratch in less than one second at a single location. If the scratch is captured well from the top view, there is a possibility of detection using the scratch detection feature. We receive numerous inquiries from industrial equipment manufacturers, and we offer explanations on usage and demonstrations during web meetings or visits involving end users at no charge. 【Software Used】 Software Used: EasyInspector710 The current 'EasyInspector2' color package can be used for scratch and defect detection.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Remote Meter Reading

We will read outdoor meter readings using AI image inspection software!

This is a request for consultation on "remote reading" of meters from a company engaged in improving water quality and ground conditions through numerical analysis. Since imaging conditions outdoors can be unstable due to factors like time of day and weather, it is crucial to establish a stable imaging environment. 【Inspection Settings and Results】 By using EasyInspector's "meter reading" function, we were able to determine two locations. In the left image, we were able to read the values, but it is necessary to verify what results will occur when the image points to values other than "2" or "8," or when the shape of the contents changes. The right image has a reading function for a rod-shaped meter, but in this case, the color difference is not very clear, resulting in a stringent setting value. If the brightness changes slightly, it is likely that the reading location will change. With some adjustments to the lighting, we might be able to relax the conditions a bit more.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Non-Detection Pixel Function

We will conduct inspections of parts produced by air conditioning equipment manufacturers using AI image inspection software!

Our company is located in Hamamatsu City, Shizuoka Prefecture, which is known for its thriving automotive parts manufacturing industry. Our main customers are manufacturers of various industrial machinery and control equipment, as well as users. We have a track record of providing support for over 1,000 cases and are developing inspection software that is easy to integrate and sold as a one-time purchase. 【Inspection Settings and Results】 By using the "Specified Color Presence Inspection Function" of EasyInspector, we conducted an inspection at one location. We used a circular frame (optional), but by enclosing the entire workpiece and masking the black background and seam areas, we believe it can also be inspected with a standard frame. In the left image, the masking function allows us to set "non-detection pixels" for areas that should not be inspected, which helps shorten the cycle time and eliminate false detections; it is a highly convenient feature. The right image shows the detection results. 【Software Used】 Software Used: EasyInspector710 The current 'EasyInspector2' color package can perform inspections for "Specified Color Presence."

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] LED Lighting Inspection on Circuit Board

We will conduct inspections of LED lighting on the circuit board using AI image inspection software.

Samples were sent from the comprehensive processing manufacturer. A simple verification was requested to determine whether the brightness at "DC14.4V is OK" and "DC9.0V is NG" can be distinguished. It was requested that if even one LED is dim during the inspection of multiple units at once, it should be judged as NG. 【Inspection Settings and Results】 We conducted an inspection to verify the brightness difference by powering at DC14.4V and DC9.0V, and we are reporting the results. The inspection was possible using the "Presence/Absence Inspection of Specified Color" feature of EasyInspector. We adjusted the lens aperture and exposure time for imaging and conducted the inspection in an environment where differences were easy to discern. By making the entire circuit board the field of view and setting inspection frames for each LED (30 units), simultaneous inspection was possible, allowing us to output which LED was NG. This time, we set the entire circuit board as the field of view and verified by applying power to one LED. The left image shows the pink inspection frame. The right image displays the green pixels detecting the specified color, while the blue color indicates the inspection frame that passed.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Matching of Printed Label Numbers

Our inspection software includes the basic functionality of saving inspection results in CSV and image formats.

The sports equipment manufacturer has been using our inspection software overseas for some time. This time, we have questions regarding the settings for "matching numbers on label printing," "smudge detection," and "checking for the presence of instruction manuals." We have agents in Malaysia and China, and we also sell inspection software for use in overseas offices. Our inspection software includes basic functions for saving inspection results in CSV and image formats, which are useful for product management across various industries. [Inspection Settings and Results] By using the "comparison with master image" function of EasyInspector, it was possible to inspect the codes and prints on 16 labels in 0.28 seconds. In image inspection, the imaging environment is the most important factor. Regarding the reasons for a dark screen during inspection, please check the following: whether there are fluorescent lights near the inspection target (this is the most common external influence); whether there are moving machines (if there are motors using electromagnetic forces, such as AC servo motors, noise may occur); and whether there is a 100V switch (which can generate electromagnetic noise).

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] LED Lighting Determination

The AI image inspection software determines the pass or fail of 48 LED locations.

This is an inquiry from a metal processing manufacturer that has already implemented our solutions. They are engaged in various business developments and will conduct a simple verification of LED lighting inspection this time. In the free sample evaluation, we will first perform a simple verification using the samples or images provided and report the verification results. During the simple verification, we will evaluate whether the desired detection/judgment can be achieved using our internal equipment. If detection or judgment is possible in the simple verification, we recommend conducting a test (feasibility verification) assuming actual operation, where we will evaluate processing time and judgment accuracy. If feasibility verification is to be conducted, you can choose to continue with us (for a fee) or use our loaned equipment for verification at your company. 【Inspection Settings and Results】 By using the "Presence of Specified Color Inspection" function of EasyInspector, it was possible to determine the pass/fail of 48 LED locations. This time, capturing the light edges clearly was challenging, so we either reduced the exposure or narrowed the aperture to capture the particles as distinctly as possible. After that, we can only search for values that can be successfully detected while tightening the color judgment tolerance. We will summarize and report the setting values for reference, but please note that the environments differ between us and you, so having the same values does not guarantee the same results.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Dimension Assessment of Automotive Parts

We will inspect whether the dimensions of automotive parts are within tolerance.

We received sample images from an automotive parts manufacturer. We will report whether the dimensions are within tolerance through a free simple verification. In the inspection process, automation is being promoted to pursue stable inspection accuracy and cost reduction. 【Inspection Settings and Results】 By using EasyInspector's "Dimension Angle Inspection" function, we were able to confirm the tolerance of a dimension at one location (left settings screen). The inspection cycle time is 0.62 seconds. We are measuring the edges of the hole and flat surface in inspection frames 001 and 002 (right detection screen). The software can calculate the difference in the X coordinate values from 002 to 001, and it is possible to convert the dimensions to mm. In the free sample evaluation, we will first conduct a simple verification using the received samples or images and report the verification results. In the simple verification, we will evaluate whether the desired detection/judgment is possible with our in-house equipment. If detection or judgment is possible in the simple verification, we recommend conducting a test (feasibility verification) assuming actual operation, and evaluating processing time and judgment accuracy. If conducting feasibility verification, you can choose whether to continue with our company (for a fee) or to use our rental equipment for verification at your company.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Forgotten Paint on Rubber Hose

We will inspect and determine the presence or absence of identification paint on the end face of the black rubber hose!

We received a contact from a manufacturer considering a poka-yoke device for forgetting to paint rubber hoses. When there is identification paint (white, yellow, red, green) on the end face of a black rubber hose approximately Φ20, it will indicate OK; if there is no identification paint, it will indicate NG during the inspection of body parts. Our website offers a free trial of inspection software online. You can actually experience the inspection software that uses AI (deep learning). 【Inspection Settings and Results】 It is possible to determine that there is one blue mark on the inspection screen. In the case of red, the count for "red" will be one, and if there is one each of white and green, they will be counted separately. Since we have trained the system to recognize the absence of marks as "none," the above image is judged to have one "none." At this stage, we are simply counting how many of each there are, so if there is more than one "none," we will set the system to determine it as a failure. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Capsules

Detect capsules with AI image inspection software!

We received a direct request from a customer who manufactures medical capsules and were conducting a preliminary verification. However, since our company does not sell FA machines, we decided to proceed with the verification through the manufacturer of the control equipment that the customer is dealing with. Our company is located in Hamamatsu City, Shizuoka Prefecture, and we have many industrial machine manufacturers as clients, primarily in the automotive industry. We have developed easy-to-integrate inspection software that is sold outright, and we have received numerous repeat orders from manufacturers of industrial machines and systems. 【Inspection Settings and Results】 As a result of processing the images received, the first image was detected normally. The second image had one false detection and one non-detection. After retraining, it was able to detect normally. After verification, we will conduct a demo at our company to explain the inspection environment and operation methods, and we will lend out demo units so that you can actually check the setup methods and inspection accuracy. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Tire Types

The AI image inspection software determines the type of tire!

We have received a simple free evaluation to determine the types of tires, such as automotive parts. This time, we tried sending photos, but sending actual samples would provide the most reliable results. In that case, you will need to send several good products and the defective work you want to detect. Please contact us for details. 【Inspection Settings and Results】 The left image shows the annotation process (the task of enclosing the parts you want to teach). The right image displays the OK screen. The tire text is being evaluated by DeepSky. We also have the capability to record images and CSV files, making integration with surrounding systems easy. The number of detectable types that can be registered per product type ranges from 1 to 1000 (here, "types" refers to classification names used during annotation, such as "screw," "desiccant," "tomato," etc. If the number of detectable types exceeds 100, the detection rate may decrease.) 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Specific Marks on Glass

We will determine whether the mark printed on the glass installed in the automobile is correct!

A manufacturer of industrial equipment, with whom we have had a relationship for some time, has been actively inquiring about "DeepSky" since its release. Our company is accepting verification and support requests from our 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】 Out of 42 images, 21 were used as training images. We inspected a total of 42 images, consisting of 21 training images and 21 untrained images. The result was that we were unable to detect only one untrained image, while all others were successfully detected. Images that were blurry or had faint prints were generally able to be judged. If we can stabilize the captured images further, we believe the accuracy could improve. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Defects in Desiccants

Detecting defects in desiccants with AI image inspection software!

This is a case that we continued to consider after a simple verification. In image inspection, the shooting environment is very important. If we can accurately capture defects, inspection is possible with a high probability. It is necessary to prepare the inspection environment within the operational range of the camera, lens, and lighting. [Inspection Settings and Results] While continuing our discussions, we found that using a backlight allowed us to clearly capture the entrapment (defect), which is expected to improve the detection rate, so we were able to provide a good report. The device used this time is a tracing table that costs several thousand yen, so I believe that sufficient effects can be obtained even with lighting that is not specifically for inspection, as long as it is a surface light source. Our company website offers a free web trial of the inspection software. You can actually experience the inspection software that uses AI (deep learning). [Software Used] Software Used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Inspection of Glossy Workpieces

We will conduct an inspection of "scratches" on glossy doors using AI image inspection software!

The photos you provided made it difficult to conduct inspections due to the shooting environment. While I was able to make a judgment as a simple inspection, it is particularly necessary to carefully consider the lighting, camera, and lens setup when dealing with glossy workpieces. [Inspection Settings and Results] You sent a total of 9 images, of which 6 were used as training images. Each of the 6 images was divided into 60 segments using image segmentation software, and 23 segments with scratches were used for training. The remaining 3 images were used for testing, and these were also divided into 60 segments before inspection. I also tried to detect dents, but I was unable to do so. It is thought that the difficulty in visually identifying certain areas may be the reason for the unsuccessful training, and I believe that defective detection can be achieved depending on the imaging environment. [Software Used] Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Lemon Grade Assessment

We will determine the grade of lemons using AI image inspection software!

In traditional rule-based image inspection, there are cases that are difficult to handle, but with "DeepSky," which uses AI (deep learning), we can apply it to various inspections that were previously impossible. Many people associate visual inspections with small and medium-sized enterprises, but the same applies to large companies, where surprisingly, automation has not progressed in certain areas. While automation in inspection lags behind production, issues such as the aging of inspectors and labor shortages have become problematic. We hope to contribute to efficient production through the automation of inspections. [Inspection Settings and Results] In the verification of lemon grade classification using the provided images, we were able to distinguish four grades with approximately 86% accuracy. Please consider this value as a reference due to the small sample size. We believe that increasing the sample size will lead to improved accuracy. With the version upgrade in 2021, we were able to incorporate a data augmentation feature for training images. This allows for efficient and stable inspections even with a small number of samples. We will continue to add various convenient features and develop user-friendly inspection software from a practical perspective.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Burrs on Truck Parts

The AI image inspection software detects burrs on truck parts.

We received multiple verification requests from a truck parts manufacturer. In the free sample evaluation, we first conduct a simple verification using the samples or images provided and report the verification results. If requested, we recommend conducting tests (feasibility verification) assuming actual operation, where we evaluate processing time and judgment accuracy. If feasibility verification is to be conducted, you can choose to continue with our company (for a fee) or use our loaned equipment for verification at your company. [Inspection Settings and Results] We verified whether we could detect burrs using DeepSky with the samples provided. As a result, we detected burrs in 54 out of 55 points, with one point not detected. All other burrs were successfully detected. With DeepSky, we can set the undetected images as additional training images, allowing us to gradually improve accuracy with each occurrence of undetectable defects after operation.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Black Spots Including Printed Parts

Detecting the presence of "printing" and "dirt" in the work!

This is a simple evaluation to detect the "black spots" dirt on workpieces, based on inquiries from manufacturers of precision cleaning agents and car chemical products. The priorities are (1) the presence or absence of lot printing, (2) the proper position of lot printing (front and back of the bottle), and (3) the automation of inspection operations for label dirt. Our company generally offers two types of inspection software: the traditional rule-based image inspection "EasyInspector" and the AI-based "DeepSky." This time, we will use DeepSky, which specializes in detecting black spot-like dirt without fixed positioning, assessing the entire screen. 【Inspection Settings and Results】 As a result, we were able to detect the "presence or absence of printing" and "dirt." We registered multiple images (5 images during verification) of the "dirt" area using the inspection software "DeepSky," performed "annotation," and conducted "learning." Since there was only one type of dirt sample, we reproduced dirt in one additional location (by applying transparent tape and recreating black spots on top of it).

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Appearance Inspection of Shumai

We will conduct appearance inspection of shumai using AI image inspection software.

This is an inquiry regarding the appearance inspection of shumai from a food manufacturer. The food industry has many products with irregular shapes, making it difficult to conduct appearance inspections using traditional rule-based methods. Recently, the number of inspection software using AI (deep learning) has increased, and there are more case studies in this industry. Inspection settings and results For the 13 patterns of samples we received this time, it was possible to distinguish between OK and NG using DeepSky. An overview of the judgment results is provided below. Since there was a concern that the sample products might deteriorate over time, we captured images with a camera of approximately 5 million pixels in advance, and during the actual verification, we downsized those images to about 1.3 million pixels for image processing. The field of view and WD (the distance from the inspection object to the lens tip) for actual implementation will be considered separately. Our inspection software has a track record of over 2,000 image inspections. We have numerous examples of inspections for metals, plastics, food, electronic substrates, pharmaceuticals, and more, so please check our website to see if there are similar cases to the inspections you are considering.

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  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Sample Book Evaluation

The AI image inspection software detects and determines the types of wood grain in the sample book!

The manufacturer that produces various sample books has also considered our inspection software. In cases like wood grain patterns, there are often discrepancies in color, texture, and design, making it difficult for traditional rule-based image inspection methods. Our website offers a free web trial of the inspection software. You can experience the inspection software that uses AI (deep learning) and make inquiries based on that experience. [Inspection Settings and Results] The images are annotations. By using software that employs AI (Deep Learning) for inspection and training it on the areas to be detected, the software itself adjusts its setting parameters and grows to recognize them. As a result of testing with the samples you provided, there were some misjudgments, but we achieved 100% detection with the trained images. Since the sample products used as teacher images were only three, there were instances of false detection for "similar colors" and "variations in wood grain." By increasing the number of teacher images, it is possible to learn various patterns of wood grain (features) and improve the accuracy rate. Additionally, capturing images separately from the left and right (with two cameras) and enlarging them is also an effective method.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Foreign Objects in Beef Hide Food Products

We will detect whether there are three types of foreign substances in food products made from cowhide!

This is an inquiry from a food manufacturer regarding whether there are any foreign substances in food products made from beef hide. We tested the provided images to see if we could detect three types of foreign substances: "corn," "straw," and "cow hair," using a simple inspection. Our inspection software has a track record of over 2,000 image inspections. We have numerous inspection cases published, including metals, plastics, food, electronic circuit boards, and pharmaceuticals, so please check our website to see if there are similar cases to the inspections you are considering. 【Inspection Settings and Results】 As a result of the verification conducted with the images you sent, it was possible to detect "corn," "straw," and "cow hair." However, it is necessary to conduct sufficient verification in anticipation of smaller detection items or different patterns (features) that may arise. We determined that detection would be difficult with full-width images due to the small size of the detection targets. This time, we conducted the verification with half-width images. We labeled the annotations as "corn" for corn, "straw" for straw, and "cow hair" for cow hair. We trained the model using 90 annotated images as teacher images. It was set up so that if any one of corn, straw, or cow hair was detected, it would be deemed a failure.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Cabbage Appearance Inspection

We will conduct an appearance inspection of cabbage using AI image inspection software.

In food manufacturing, irregularly shaped work (ingredients) is commonplace, and even minor defects or foreign matter can lead to significant accidents. This time, we have received a request for a simple inspection of food. The ongoing societal issues of a declining workforce and the aging of skilled workers show no signs of stopping, and efforts to support productivity improvement are increasingly in demand. Image inspection technology has gradually become more sophisticated. Please consider the introduction of image inspection to maintain the Japanese quality that allows us to consume safe and secure food. 【Inspection Settings and Results】 This is a verification based on the images provided. The areas of interest to be detected were enclosed in frames and labeled by type. This time, we annotated the images into four categories: "discoloration," "flower buds," "length," and "length 2." Since the verification was conducted by dividing the existing images into labeled and unlabeled data, the accuracy was not very high, but it can be inferred that increasing the sample size will improve accuracy to some extent. 【Software Used】 Software used: DeepSky Learning Edition

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  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Appearance Inspection of Chinese Cabbage

We will conduct an appearance inspection of cabbage using AI image inspection software!

The introduction of appearance inspection systems is rapidly increasing even among food manufacturers. It has been considered difficult to conduct appearance inspections due to unstable shapes, but we expect inquiries to continue to rise due to technological advancements and labor shortages caused by population decline. It is our mission to contribute to the manufacturing industry, which is directly linked to our comfortable lives. 【Inspection Settings and Results】 A total of 31 images were used as training data, consisting of 10 OK and 29 NG samples. As shown in the left image, the areas of interest to be detected were framed and labeled by type. The label names were set as follows. There were no false detections in the judgment based on the training data. Among the 61 non-training images, there were 15 instances where NG was judged as OK. For workpieces with unstable shapes, increasing the number of training images and conducting additional learning can improve detection accuracy. 【Software and Equipment Used】 Software Used: DeepSky Learning Version Number of Inspection Points: 1 point searching for defects across the entire screen Camera Resolution: 1.3 million pixels Lens Focal Length: 12mm

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  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Black Parts on a Black Background

It enables the detection of black foreign objects and parts on a black background, which has been considered difficult to detect until now.

This is an inquiry from a manufacturer of resin-molded parts for automotive interior components, with whom we have had transactions in the past. Detecting black foreign objects or parts on a black background has been considered a challenging inspection task until now. The image inspection software DeepSky, which uses AI (deep learning), is capable of recognizing such similarly colored parts and foreign objects. 【Inspection Settings and Results】 Using a 1.3-megapixel camera, we captured approximately 1/4 of the overall field of view and conducted learning and detection. As a result, it was possible to identify the types of clips and the number of tackers under the verification environment. However, for items like fasteners attached to sloped surfaces where tackers are difficult to see, detection is likely to be challenging, so adjustments to the camera angle will be necessary. We categorized the labels into 11 types (naming and registering the items we want to find). We conducted simple tests after training with 13 teacher images for 1600 steps. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Hair Contamination in Food

We will detect and determine hair mixed in frozen food!

In food manufacturing, the presence of hair can lead to significant incidents. For inquiries regarding food or raw items, we may ask you to send images. In such cases, if you could provide photos with good lighting and focus to clearly capture the area of concern (defect), we can conduct an inspection. This time, we received an image with hair placed on frozen food. 【Inspection Settings and Results】 In the pattern of frozen food, the detection results were favorable. When in a frozen state, the overall appearance is whitish, which provides good contrast with black hair. However, I believe that even at room temperature, there is a possibility of detection if we simply increase the number of training images. By increasing the number of training images and learning steps, DeepSky's strength lies in its ability to improve accuracy through continued learning. 【Software Used】 Software Used: DeepSky Learning Version Number of Inspection Points: 1 location to find hair from the entire screen

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Detection of Foreign Objects in Pleated Filters

Detect foreign objects in tubular pleated filters using AI image inspection software!

This is a communication from a trading company we have been dealing with for some time. "Foreign substances" will be detected. We have received inquiries from various customers, including industrial equipment manufacturers, trading companies, and end users. 【Inspection Settings and Results】 When we actually applied image processing, there was some variation in detection depending on the angle, but foreign substances of about 2mm could be detected within a field of view of approximately 250mm. Very small foreign substances, such as tiny black dots or hairs, could be detected within a field of view of about 50mm. 【Software and Equipment Used】 Software Used: DeepSky Learning Field of View: 50mm Minimum Size of Inspection Target: 2mm Number of Inspection Points: 1 location to find foreign substances across the entire screen Camera Resolution: 1.3 million pixels Lens Focal Length: 8mm Lighting: Indoor fluorescent lights

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Inspecting Paint Defects on Metal

We will inspect the painted metal work for "paint splatter," "oil-like residues," "scratches," "dents," and "liquid drips."

This is an inquiry from a manufacturer of industrial machinery asking if inspections can be conducted on a conveyor. 【Inspection Settings and Results】 Using DeepSky's inspection capabilities, it was possible to perform evaluations on the conveyor. The left image shows the process of enclosing the area of interest, referred to as "annotation." The right image displays the "detection frame." By separating the settings for overall defects, such as oil adhesion and roughness, from partial defects like scratches, drips, and bumps, we achieved good evaluation results.

  • Image Processing Software
  • Visual inspection software

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[AI Image Inspection Case] Judgment of Sewing Product Implementation

We will automate the inspection process carried out by operators using jigs in multiple stages!

The curtains installed inside vehicles such as cars, buses, and trucks are folded in an accordion style. If the various components, such as the belts called "hooks" and "tassels," as well as "Velcro," are not attached in the specified positions, the product will not pass inspection. There is a request to automate the current process where workers use jigs to inspect multiple times. 【Inspection Settings and Results】 The inspection was conducted using the inspection software "DeepSky." First, the components to be identified were annotated (left image). To help the software recognize the inspection areas, we annotated 10 good sample images divided into five categories: belts, part A, part B, Velcro, and product tags. Next, the areas where these components should be installed were specified (right image). Since the curtains are accordion-style, a proposal was made to use jigs for fixing in order to capture the workpiece in the correct specified position. It was possible to accurately determine whether the specified components were in the designated locations, marking it as OK if present and NG if not.

  • Image Processing Software
  • Visual inspection software

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