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

[AI Image Inspection Case] Confirmation of Check Sheet (2)

We will check the check sheets filled out by people using AI image inspection software!

The fact that 'there are inevitably oversights by operators during visual inspections' can occur not only in factory production processes but also in other areas. This inquiry comes from an industrial machinery manufacturer, but the verification of check sheets filled out by humans is a common issue across all industries. [Inspection Settings and Results] We printed the data from the check sheet you sent and conducted tests. We verified the presence or absence of checks on paper. By using EasyInspector's 'OCR Pro' feature, we were able to read five holes or symbols in just 0.62 seconds. After a simple verification, we will conduct an in-house demonstration. Additionally, we offer a web video demonstration on our website, a 60-day trial software download, and a free evaluation service for inspection items, all aimed at providing information and support to help customers easily implement the inspection system. We look forward to your inquiries and hope you take advantage of the above services. If you have any requests or questions, please feel free to contact us anytime.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Detection of Battery Orientation

After storing 12 or 24 batteries in the gold box, it is a check to ensure there are no mistakes in the orientation of the batteries.

We received an inquiry from a battery manufacturer stating, "There is a white + mark on the cover, and we want to determine if there is any mistake in orientation based on its position." They also expressed a desire to take photos while holding a tablet and camera by hand. 【Inspection Settings and Results】 By using the "Presence of Specified Color Inspection" feature of EasyInspector, we were able to determine the orientation of the parts. We reported on a simple verification. Inspection frames were set up in multiple locations (this time at six locations: including two NG locations). We set "white" as the specified color and conducted the inspection based on the extent to which the specified color was detected within the inspection frame. When using EasyInspector, it is essential to fix the camera. While it is possible to take photos with a tablet, it needs to be secured. 【Software Used】 Software used: EasyInspector710 The current 'EasyInspector2' color package can perform inspections for the "Presence of Specified Color."

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Judgment of Paper Tubes

We will perform judgment of paper tubes using AI image inspection software.

This is a free simple verification based on the sample images you provided. It is from a manufacturer of industrial control equipment with whom we have had transactions in the past. In image inspection, the imaging environment is a very important point. This time, the accuracy of the inspection varied depending on the captured images. 【Inspection Settings and Results】 We were unable to obtain good results with the images as they were, so we cropped only the areas to be evaluated and conducted the verification. As a result, in the case of the images we verified this time, if we could set the field of view appropriately for the judgment of the paper tube, it was possible to make a judgment. Since there were few OK images, we created mirrored images to use for verification. We used a total of 20 images for training, consisting of 10 OK images and 10 NG images. For the validation of the judgment, we used 2 OK images and 2 NG images that were not used in the training, for a total of 4 images. 【Software Used】 Software used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Overflow of Food Ingredients

We will inspect and determine the extent to which the food in the tray is overflowing.

We conducted a simple inspection of the extent of food overflow in trays from a food manufacturer using the rule-based "EasyInspector" and reported our findings. However, detecting overflow on trays with a blue background and white patterns proved difficult, so we decided to re-verify using "DeepSky," which utilizes AI (deep learning). Our company website offers a free web trial of the inspection software. You can actually experience the inspection software that uses AI (deep learning). 【Inspection Settings and Results】 We created several patterns of defective conditions using the samples we have on hand and were able to detect ingredient overflow by training on those images. However, in this case, various patterns of ingredients and defects are expected, so a large amount of training data is necessary to achieve sufficient detection results. With the version upgrade in 2021, we were able to incorporate a data augmentation feature for training images. We will continue to add various convenient features and develop user-friendly inspection software from a practical perspective. 【Software Used】 Software Used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Strawberry Harvesting Season

We will determine the harvest time of strawberries using AI image inspection software!

At the request of a manufacturer of industrial equipment, we conducted a simple evaluation to determine the harvest timing of strawberries. We used 58 sample images for the inspection. (34 strawberries were classified as OK and 24 as NG) 【Inspection Settings and Results】 As a result, all "harvestable strawberries" were correctly detected. Teacher Images: Correct Judgment 100% (20/20) Incorrect Judgment 0% (0/20) Unlearned Images: 94% (32/38) 6% (2/38) Total: 96% (56/58) 4% (2/58) However, among the strawberries classified as NG, two strawberries that appeared close to OK when viewed by the human eye were mistakenly classified as harvestable. (1) Still pinkish in color, therefore not harvestable... NG1 (Pink) (2) Still white or green, therefore not harvestable... NG2 (White or Green) (3) Strawberries that can be harvested... Harvest OK By creating three types of labels and training the software, it will adjust its own setting parameters and improve recognition. The images are annotated.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Waste Liquid Treatment Judgment

We will conduct waste liquid processing (monitoring of coagulation state) using AI image inspection software!

We received an inquiry from a manufacturer of various machine parts regarding bearings. They currently monitor the treatment of waste liquid through visual inspection, and it is said that when aggregation occurs from the state shown in the left four images below to the state in the right four images, it is considered acceptable. Although there is a roof, it is not an indoor environment, and the imaging conditions for inspection change depending on the time and weather. 【Inspection Settings and Results】 We set 24 images, including the ones above, as training images, annotated them all, and were able to make judgments. With the version upgrade in 2021, we were able to incorporate a data augmentation feature for training images. We will continue to develop inspection software that is user-friendly and practical by adding various convenient features. The strength of AI (deep learning) image inspection software compared to traditional rule-based image inspection software is its ability to perform inspections even with differences in brightness and imaging environments. Inspection software can be beneficial in various industries and processes. 【Inspection Software】 Software used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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Inspection Technique: Defective Positions of Teacher Images

We will provide solid support regarding settings such as what kind of teacher images to use!

We received an inquiry from a customer who manufactures automotive parts and industrial machinery regarding the settings of DeepSky. They asked, "I thought the system was searching the entire screen based on the characteristics of the annotated area I set, but do you also remember any tendencies about where it tends to appear in the field of view?" 【Inspection Settings and Results】 We arrange squares of the same color and size and annotate only the upper part for training (see the image in the top left). In the image on the top right, we can find only the upper part. In the lower left image, we can also find only the upper part. However, in the right image, we could not find anything from the lower part. If the system can only find data that closely matches the teacher due to overfitting, the situation changes a bit. However, the position of the items we want to detect, such as defects, greatly affects inspection accuracy. It is necessary to use teacher images with various positions, orientations, and angles. As of 2021, DeepSky has been equipped with a teacher image augmentation feature. We can augment images of defects that rarely appear by flipping or rotating them in all directions and using brightness or Gaussian noise.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Position of Press Felt Parts

We will check if the installation position of the clip for the press felt parts is correct!

Press felt parts for automotive components may vary in the presence or absence of holes and the positioning of parts due to differences in specifications. However, in the case of similar products, accidents have occurred where similar but incorrect items were shipped because they looked almost identical. This time, we will verify whether the installation position of the clips is correct. 【Inspection Settings and Results】 We were able to distinguish between two types of clips in the overall view. It seemed challenging to determine the presence of the fastener's tacker or the text on the label from the overall view, so I suggested that using two cameras for one workpiece would be a more practical approach. The image shows the setup for inspecting whether the correct type of clip is in the correct position. The outer frame indicates the correctness of the installation position, while the inner frame determines whether the part is correct. 【Software Used】 Software Used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Adhesive Application Cut-off

We will inspect for adhesive application defects using AI image inspection software!

This is a request for evaluation from a manufacturer of audio systems such as speakers. Before the inquiry, line workers were conducting visual inspections of about 10,000 units a day. Due to the black resin and dark adhesive, the work had characteristics that made it very difficult to see, both visually and with cameras. 【Inspection Setup and Results】 Since it was difficult to conduct inspections with EasyInspector, we used a product that utilizes deep learning called DeepSky. Initially, we tried training with the existing images, and detection was possible; however, the number of data points was small, and the images were very difficult to inspect, so I believe more detailed verification is needed in terms of accuracy. Nevertheless, detection was achieved to some extent, and I am reporting the above image as documentation of that process. 【Software Used】 Software used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
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Technical Support: Accuracy and Resolution

We also provide support for annotation methods and capturing teacher images that improve detection accuracy.

We received an inquiry regarding the detection method of DeepSky from a pharmaceutical company we have been in contact with for some time. 【Test Settings and Results】 Image B is one of the four divided parts. The resolution is simply one-fourth. Assuming the area of defects in the entire field of view is 1, the area of defects in the entire field of view of Image B would be 4. Since the "target object" is significantly larger in the overall image, it becomes easier to detect in Image B, even though its resolution is lower. This is why the importance of resolution itself is lower in deep learning. 【Software Used】 Software used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Detection of Foreign Objects in Bento Boxes

We attempted a verification assuming the contamination of "hair," "plastic pieces," "vinyl pieces," and "insects."

In the food industry, contamination with foreign substances has long been a significant issue. This time, we conducted inspections using a software called DeepSky, which utilizes AI (Deep Learning). The image in the upper left is called an annotation, where we train the software to recognize specific areas (foreign substances) by adjusting its own setting parameters. The software detects "hair," "plastic," and "insects" in the images. However, it was unable to identify the insect mixed in with the sesame seeds on the rice. It is necessary to capture a clear distinction between the sesame and the insect. Software used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Detection of Foreign Objects in Cylindrical Filters

Detects foreign substances (fibers, dust, hair, and particulate matter) in cylindrical filters.

In visual inspections conducted by workers, there is often variability in the criteria for determining "good products" and "defective products" among inspectors, and the more ambiguous the criteria, the more inconsistent the inspection results tend to be. Please consider a stable and efficient inspection using an image inspection system. The image on the left shows the environment with the camera, lens, and lighting. The image on the right depicts the task known as "annotation," which involves framing the areas to be detected. By "training" the framed areas, we were able to detect the target objects within the inspection images. The inspection items were placed on a rotating platform, and detection verification was conducted while rotating. During the verification, it was assumed that the inspection would take about 60 seconds per item. As for dust, it could not be visually confirmed as defective, so settings and detection could not be performed. If defective parts cannot be photographed, the inspection becomes challenging. Creative solutions are needed for capturing images.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Presence or Absence of Transparent Varnish

We will inspect the presence or absence of transparent varnish using AI image inspection software!

We received an inquiry from a manufacturer of containers and packaging materials regarding the presence or absence of transparent varnish. Detecting the presence of transparent varnish is difficult with conventional image processing methods like EasyInspector, and if we were to make a suggestion, it would be to use a software called DeepSky that utilizes deep learning. 【Inspection Settings and Results】 Since we only have two images for training data, the results will be for reference only. However, by training the model on images with and without varnish, there is a possibility of distinguishing the presence of varnish as shown in the images. The images you provided were likely taken under stable conditions regarding lighting, positioning, and camera distance. We would like to request an increase in the number of NG and OK images using the same imaging method for further validation. 【Software Used】 Software used: DeepSky

Company：スカイロジック
Price：Other

Image Processing Software
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[Technical Support] How to Generate Parameters for DeepSky

If you have any questions about results or settings that you cannot accept, please feel free to contact us.

The grain dryer manufacturer experienced the web trial of our inspection software DeepSky, which uses AI (deep learning) from our website, but did not obtain satisfactory inspection results. We provided guidance on the method for generating parameters. While personnel familiar with deep learning inspections can conduct inspections smoothly, it is natural that first-time users may not achieve the desired results. If you have any questions about unsatisfactory results or the settings, please feel free to contact us. 【Inspection Settings and Results】 We enclosed the target areas to be detected in frames and labeled them by type. This time, we used seven pieces of training data consisting of five types: the numbers 1 to 4 and one without a number. All images correctly identified the targets. 【Software Used】 Software used: DeepSky Number of inspection points: 2 locations, recognizing the numbers in two areas on the screen.

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Inspection of Foreign Objects and Dirt on Non-Woven Fabrics

The AI image inspection software detects foreign substances and dirt in non-woven fabric!

We received sample images of non-woven fabric from various manufacturers of textile products and non-woven fabric. This is a request for a free evaluation to find foreign substances and dirt. Sending actual samples has become stricter recently due to compliance and security concerns. If you can send samples to our company, we can verify and provide guidance on aspects such as lighting, cameras, lenses, and the distance to the work. 【Inspection Settings and Results】 Using the 23 images sent, we were able to detect defective areas. The left image shows the annotation work of enclosing the areas we want to detect with rectangles. The right image shows the detection frames of the inspection results. Out of the 23 images, 16 were used as training images. (There are 21 images, and we processed 2 similar NG images at our company.) We evaluated a total of 23 images, consisting of 16 training images (2 OK / 14 NG) and 7 untrained images (1 OK / 6 NG), and we are reporting the results.

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Verification Inspection of Thermistor Adhesive Application

We will conduct various tests using AI image inspection software!

We are considering the introduction of various inspections from a FA control equipment manufacturer. We received an inquiry about automating inspections for "presence of adhesive," "fit claw engagement status," "thermistor adhesive application confirmation," "presence of ring components," "nameplate," "thermistor bending," "presence of screws," "excess/insufficient solder," "presence of lead wires," "solder rise," and "quality of thermal welding." [Inspection Settings and Results] Inspection is likely possible for all inspection items. The initial verification report will be a simple evaluation based solely on pass/fail judgment. The basic concept of image processing using deep learning is to "find what has been taught." For example, when performing "thermistor adhesive application confirmation," you would specify the condition of good products (left) and defective products (right) and conduct learning to distinguish between the presence and absence of adhesive. When considering implementation, please utilize equipment loan services, and ensure that the customer confirms the actual feasibility of inspections.

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Detection of Black Spots on Oyster Flesh and Eggs

We will conduct defect assessment of shucked oysters using AI image inspection software!

Seafood and fruits have a rough similarity in shape, but in image inspection, their shapes are not stable, and variations in size and ripeness can change their color and bulge, making them difficult to assess. Our inspection software, DeepSky, excels in inspecting items with slightly different shapes. This time, we evaluated the defect detection of shucked oysters based on an inquiry from a manufacturer that produces automation robots used in food factories. Since it is not the shipping season for oysters, the inspection was conducted using the images provided. 【Inspection Settings and Results】 Upon verifying the sample images you sent, we were able to detect eggs and black spots. The inspection was performed using software that employs 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. Our software does not only detect based on color; it also incorporates texture (surface quality) into its judgment. Additionally, there is no need for fixed positioning, allowing for detection even if multiple oysters flow on a conveyor in various positions and orientations.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Judging Defects in Fabric

We conducted a free evaluation of the detection of "discoloration," "thread pulling," and "holes" in three types of fabric: "quilt fabric," "flower pattern," and "solid color."

The HDD was sent for testing with sample images. 【Inspection Settings and Results】 The left image shows the annotations, while the right image represents the detection frames. By using DeepSky's inspection features, we were able to identify defects in the fabric, such as "discoloration," "thread pulling," and "holes." The overall shooting environment of the images provided was somewhat dark, and as a result, the judgments were generally correct, but there were two misjudgments regarding the floral patterns. If the images could be captured more clearly with better lighting conditions, it would lead to higher accuracy in the assessments. 【Software Used】 Software Used: DeepSky Number of Inspection Points: Entire screen (discoloration, thread pulling, holes)

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Inspecting holes in a workpiece using underwater bubbles

We will check if there are any holes in the flexible hose!

A manufacturer that handles fittings for metal products and resin products is currently inspecting for holes caused by bubbles underwater. The appearance of bubbles varies in quantity, size, and continuity, and floating debris underwater can resemble bubbles, leading to many misjudgments. This inquiry is regarding a switch from the current image inspection software. We conducted a free evaluation of the four types of images you sent: "large, medium, small, and very small." 【Inspection Settings and Results】 We were able to make good judgments using a method to inspect for the presence of bubbles floating on the water's surface. The left image is an annotated teacher image for training purposes. The right image shows the detection frame display. The rising speed of bubbles underwater is very fast, and with frame-by-frame shooting every 0.3 seconds, there was a risk of missing captures and inspections. DeepSky allows for continuous shooting settings, and inspections without fixed positions during conveyor or work processes are also possible, but depending on the computer's specifications, it typically results in still image frame-by-frame shooting every 0.2 to 0.3 seconds. 【Software Used】 Software Used: DeepSky (Training Version) Number of Inspection Points: One location at the top of the screen (entire water surface)

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Identifying Types of Trays

We will conduct inspections to distinguish between five types of trays using AI image inspection software.

The use of dedicated trays to place workpieces in each grid during manufacturing and shipping is commonly seen in various situations. While it can be challenging to position workpieces that move within the tray, our inspection software, DeepSk, can assist with such inspections. In the verification with the images you provided, we set up an inspection using AI with DeepSky to distinguish between five types of trays. We trained the model with 70 images (14 images for each of the 5 types) out of a total of 277 images. 【Inspection Settings and Results】 We inspected a total of 277 images, consisting of 70 training images and 207 untrained images. The red box in the right image shows how many of each tray were detected. In this setup, if Tray 1 is detected once, it is set to "pass." The results showed 4 false detections among the untrained images, while the remaining 273 images were successfully detected. By retraining on the falsely detected images, the inspection accuracy can be further improved. The ability to retrain is a strength of inspection software that uses AI. The initial evaluation report on detection capability is kept simple. 【Software Used】 Software used: DeepSky Learning Edition

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Adhesive Stringing

We have received a request from a camera manufacturer to detect "adhesive stringing" that occurs during manufacturing.

Out of the 84 sample images you sent (39 NG / 45 OK), 50 images (25 each) were used for training as teacher images. The remaining untrained images were used as test images. 【Inspection Settings and Results】 By using DeepSky's inspection function, we were able to determine the Ito-biki in 0.23 seconds. The results of inspecting the teacher images and the remaining 34 test images showed a correct answer rate of 100%. The number at the top of the image detection frame indicates the AI's confidence level in percentage (number of recognition points). 【Software Used】 Software used: DeepSky Learning Edition

Company：スカイロジック
Price：Other

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[AI Image Inspection Case] Film Identification

We distinguish various defects that occur during film manufacturing. This time, we created and set labels for seven defects and good products.

We received 100 sample images from a manufacturer that produces high-quality films for verification. For the free evaluation of DeepSky, it is necessary to send photos of various defective shapes of the work. 【Inspection Settings and Results】 By using DeepSky's inspection function, we were able to detect the presence of various shapes of defects with an inspection cycle of 0.28 seconds per instance. The left image shows the settings, while the right image outlines the areas we want to identify and labels them for learning purposes. - We created a setting where if any NG (defective) item is detected, it is marked as a failure; if only OK items are detected or nothing is detected, it is marked as a pass. By training the software with OK and NG, we have been able to conduct inspections that meet our customers' requirements. Our website offers a trial service for DeepSky. Please take advantage of it. 【Software Used】 Software Used: DeepSky Learning Version

Company：スカイロジック
Price：Other

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[AI Image Inspection Case] Color Identification Inspection

We identify the colors of internal parts of automotive products and make judgments! We detect similar different items because they look almost the same!

The seat designs of automobiles, buses, airplanes, and other vehicles may vary in design and size due to different specifications, and the internal components also change depending on the grade. In the case of similar products, accidents occurred where similar but different items were shipped because they looked almost identical. 【Inspection Settings and Results】 An evaluation was conducted using DeepSky. On the left is the annotation image (the teacher image that teaches the part to be detected), and on the right is the inspection result image. This time, since it was a work that could not be externally leaked, our company used a model and proposed an annotation method. Currently, for consideration of implementation, we are offering a free rental service for demo units. The number of demo units is limited, so depending on the reservation status, there may be delays. We kindly ask you to make your reservations as early as possible. 【Software and Equipment Used】 Software used: DeepSky Field of view: 100 x 80mm Minimum size of inspection target: 5mm Number of inspection points: 4 (Label 8) Camera resolution: 1.3 million pixels Lens focal length: 12mm Distance between lens and product: 450mm Lighting: Indoor fluorescent lights

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Multiple Inspections Including the Back Tack of the Cabinet

This is an inspection regarding the back tacker, front door color, peel, internal label, presence or absence of screws, Urea screws, and the implementation of the connection part and bump part.

There was a request for evaluation of image inspection in multiple areas to reduce personnel and improve operational efficiency in the cabinet manufacturing process. 【Inspection Settings and Results】 By using EasyInspector's "Scratch Detection" function and "Presence of Specified Color Inspection" function, we were able to detect 20 differences and determine visually similar items (different products) for each category in less than one second. 【Software and Equipment Used】 Software Used: EasyInspector710 Field of View: Various field of views Minimum Size of Inspection Target: 2mm Number of Inspection Points: 20 Camera Resolution: 5 Megapixels GigE Lens Focal Length: 25mm Distance from Lens to Product: 1200mm Lighting: Linear fluorescent lights, etc. Distance from Lighting to Inspection Item: Not recorded The current 'EasyInspector2' color package can inspect for the presence of specified colors.

Company：スカイロジック
Price：Other

Image Processing Software
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[AI Image Inspection Case] Card Recognition OCR

We are utilizing our EasyInspector before packaging to record the issued cards.

Children have loved card games both now and in the past. Many of you may have collected cards when you were young. Some printing manufacturers produce cards specifically for card games. Once packaged, it becomes impossible to know which cards are inside. Therefore, we utilize our EasyInspector to keep a record of the issued cards before packaging. Inspection settings and results By using the "OCR Pro" feature of EasyInspector, we were able to read a single location with a 7-character format (card number) in 0.19 seconds. The OCR Pro feature includes binarization and dictionary learning functions. It can read not only existing fonts but also other types, although it may become difficult to read if the lines of the characters are broken or if adjacent characters are connected. Please contact us for inquiries about the extent of readability.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Counting the Number of Glass Sheets

The AI image inspection software counts the number of stacked glass sheets.

Some production technology personnel believe that it is difficult to inspect work with high visibility, such as glass, due to halation. Our company also proposes inspection methods using cameras, lenses, and lighting that can be used for photography. 【Inspection Settings and Results】 By using the "Luminance Change Inspection" function of EasyInspector, we were able to verify the number of stacked glass sheets and make a judgment in 0.04 seconds. We detected the black areas and accurately counted the number of sheets. However, we could not make accurate judgments (detect differences in brightness) in areas where light was not clearly shining, making lighting an important factor in this case as well. 【Software Used】 Software Used: EasyInspector300 Number of Inspection Points: 1

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Inspecting Logo Mark Inversion

Detects mistakes in the placement of rectangular and square logo marks!

There are tasks involving the application of logo marks from various manufacturers. It is a common mistake to accidentally apply rectangular or square logo marks in reverse. Our company supports you with image inspection to ensure that your important logo is shipped with high design quality and beauty. 【Inspection Settings and Results】 By using the "Comparison with Master Image" feature of EasyInspector, we were able to determine a labeling error in less than 3.56 seconds. The "OK" and "NG" images provided had differences in field of view, brightness, and brightness direction, so we adjusted the "Shift Correction" feature and the settings for "Color Judgment Tolerance Range." It is necessary to prepare the inspection environment during actual operation. (Fixing camera position and orientation, fixing lighting position and intensity, fixing inspection item placement, etc.) 【Software Used】 Software Used: EasyInspector710 The current 'EasyInspector2' color package can perform inspections using the "Comparison with Master Image" feature.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Panel Hole Presence Inspection

We will conduct an inspection of a panel with two large holes and 27 small holes using AI image inspection software!

In the automotive manufacturing industry, the panels to be installed have many holes, and because there are similar panels, if there is any issue with the presence or position of even one hole, the product cannot be deemed acceptable. Therefore, we considered using image recognition technology. [Inspection Settings and Results] We included a panel with two large holes and 27 small holes within the field of view. For the larger holes, we set up the EasyInspector's "Color Comparison Inspection" feature to detect the "pink color" of the holes. For the smaller holes, we used the "Defect Inspection" feature to detect white defects. The holes themselves were clearly captured using backlight illumination, allowing for accurate inspection even if the position of the holes was off by 50mm. The red areas on the right side of the image indicate where the holes were detected.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Inspection of Bumps on Coated Surfaces

The AI image inspection software detects and determines defects in automotive parts caused by painting errors!

When inspecting automotive parts after painting, there are instances where defects caused by painting errors result in the shipment of defective products. We wanted to enable the detection of these defects through image inspection. In automotive parts manufacturing, post-painting defect inspection is considered crucial for product assembly, leading us to consider the introduction of image processing to ensure accuracy. 【Inspection Setup and Results】 Using the "Scratch and Defect Inspection" feature of EasyInspector, we set up inspection frames to detect bright pixels compared to surrounding pixels and dark pixels at the same position, allowing detection regardless of which type is present. Even in cases where the background has a striped pattern, we were able to detect defects as small as 1mm by modifying the settings.

Company：スカイロジック
Price：Other

Image Processing Software
Visual inspection software

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[AI Image Inspection Case] Inspection for Missing Label Printing, Smudging, and Black Spot Detection

Skylogic's AI image inspection software solves the problem of shipping defective prints due to missing or faded print and black spots!

In the label manufacturing industry, such as for product descriptions, productivity is increased by printing multiple labels at once. On the other hand, issues such as missing prints, smudges, and defects due to black spots have also arisen during printing. This problem of defective shipments is one that many label manufacturing companies face, and image processing software has been used as a means of improvement. 【Inspection Settings and Results】 By using the "Comparison with Master Image" feature of EasyInspector, three inspection frames were set for a single label to establish pass/fail criteria for missing prints, smudges, and black spots, detecting multiple defective areas. In the image above, the smudged area (NG) is highlighted in red, while the OK areas remain unchanged. 【Software and Equipment Used】 Software Used: EasyInspector710 Field of View: 60x 70mm Minimum Size of Inspection Target: Approximately 5mm Number of Inspection Locations: 3 Camera Resolution: 1.3 Megapixels Lens Focal Length: 35mm Distance Between Lens and Product: Approximately 360mm Lighting: Indoor Lighting Current inspections can be performed with the 'EasyInspector2' color package using the "Comparison with Master Image" feature.

Company：スカイロジック
Price：Other

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

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