We have compiled a list of manufacturers, distributors, product information, reference prices, and rankings for Visual inspection software.
ipros is IPROS GMS IPROS One of the largest technical database sites in Japan that collects information on.

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

91~120 item / All 466 items

Displayed results

[AI Image Inspection Case] Inspection of Hole Position and Presence in Rubber Flanges

The AI image inspection software detects and determines the presence and position of holes in circular rubber flanges!

This is a request for image assessment to check for holes in a circular rubber flange. It is noted that defective products either have no holes (clear points) or have very few holes, or the holes are small. Additionally, there are concerns about detecting burrs, defects on the outer circumference, and debris (clear points outside the hole positions). A sample has been sent from a company involved in ground investigation and ground improvement. 【Inspection Settings and Results】 We conducted verification of hole presence and position inspection using the sample provided. As a result, we were able to detect the hole areas and determine their positions and presence. However, if the position of the holes is also to be inspected, the following conditions are necessary: the inspection item should be fixed in place using an L-shaped fixture or similar. The orientation of the inspection item should also be set to be approximately the same. Regarding the orientation of the inspection item, please align it roughly based on the areas where numbers or letters are displayed on the surface. Using the "Presence of Specified Color Inspection" function of EasyInspector, we were able to detect the presence or absence of holes and differences at five locations, and we could determine visually similar similar products (different items) in 0.59 seconds.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Quantification of Surface Processing

We quantify the surface roughness of the coating layer on resin products using AI image inspection software!

The cellulose fiber resin manufacturer has delicate surface processing technology. This time, we received an inquiry about quantifying the surface roughness of the coating layer through inspection, and we decided to test whether the surface roughness could be determined through image inspection instead of visual confirmation (sensory evaluation). 【Inspection Setup and Results】 By using the "Presence or Absence of Specified Color" function of EasyInspector, we were able to quantify the differences in texture at one location (overall). The results were better when judged using EasyInspector, which allows for detailed settings including stability and color tolerance ranges. The settings for how much to detect as black and what shade to consider as black were done using EasyInspector. 【Software Used】 Software Used: EasyInspector710 The current 'EasyInspector2' color package can be used for inspection with the "Presence or Absence of Specified Color."

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Inspection of Typos and Misspellings in Kraft Paper Bags

The AI image inspection software evaluates the printed content, such as text, on kraft paper bags!

A manufacturer that produces craft paper bags for brown rice was considering using our image inspection software to evaluate the printed content, such as text, on the craft paper bags at their factory. Currently, multiple factory personnel are inspecting the printed content each time, and there are instances where mistakes, such as typos, go unnoticed, leading to incorrect products being delivered to customers. Therefore, they were thinking of transitioning to machine-based inspection to prevent the outflow of incorrect items and reduce the burden on personnel. [Inspection Settings and Results] By using the "Comparison with Master Image" feature of EasyInspector, we were able to inspect the differences in four areas of text in 0.23 seconds. We set the field of view to capture the entire printed area for verification. In the left image, the parts that differ from the master image (settings screen) are highlighted in red as NG (not good) detections. [Software Used] Software used: EasyInspector The current 'EasyInspector2' color package allows for inspection using the "Comparison with Master Image" feature.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Determination of Checklist Signatures

We will conduct an inspection using AI image inspection software to check for the presence or absence of signatures on the production management checklist!

The manufacturer, which designs various devices such as medical equipment and infrastructure, has been a business partner for some time. This time, we received a request for a simple verification inspection to check the signatures on the production management checklist. 【Inspection Setup and Results】 By using the "Presence of Specified Color Inspection" feature of EasyInspector, we detected the presence or absence of signatures in four locations. The left image shows the master image (inspection frame setup screen). It was set up so that if the color of the detected signature within the installed frame is within the reference value, it is marked as OK; otherwise, it is marked as NG. The right image shows that the blue frame indicates pass, while the red frame indicates fail. The areas with signatures are judged as OK, while the empty areas are judged as NG. By setting up an inspection frame in the areas to be checked, the presence or absence of entries can be inspected. A maximum of 999 inspection frames can be installed. 【Software Used】 Software used: EasyInspector710 The current 'EasyInspector2' color package can perform inspections for the "Presence of Specified Color."

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Size of Annotation

I will share the key points for "annotation" to teach the AI where to detect.

This is a support case for a customer who has actually implemented DeepSky. We provided guidance to increase the detection rate. The "annotation" used to teach the AI where to detect is crucial for inspection accuracy. The image below shows annotations that had a low detection rate. We advised that annotations that are too large or too small decrease the detection rate. Our company offers 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 set the judgment to "fail" after detecting one or more defective areas. (The inspected images were unknown images different from the trained teacher images.) We inspected 32 unknown images (16 good products / 16 defective products) and achieved 30 correct judgments and 2 incorrect judgments (we failed to detect defects, and all good products were correctly judged). *We also inspected the teacher images, but there were 2 false detections. It is likely that increasing the number of training images and the training time will improve detection. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Washer Presence Inspection

The AI image inspection software detects the presence or absence of washers!

We received a request for a simple verification from a major general electronics manufacturer that has contacted us before regarding DeepSky. The presence or absence of washers is an area where DeepSky excels. We recommend trying out the web version to experience AI (deep learning) more closely. 【Inspection Settings and Results】 From the images provided, we used 10 OK images and 10 NG images, totaling 20 images, as training data. We then evaluated 5 OK images and 5 NG images, totaling 10 images, from the remaining images as unknown data. In this verification, there were no false detections, and we were able to correctly classify all 30 images. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Inspection of Washer's Curling Presence or Absence

We will process the texture of the washer to detect the sagging parts!

This is a specific consultation regarding the operation after a simple verification from a manufacturer of precision processed products such as automotive parts. We will create a setup to detect the blurred areas of a washer through image processing. In the free sample evaluation, we will first conduct 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 is possible using our in-house equipment. If detection or judgment is successful 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 our company (for a fee) or verify using our loaned equipment at your company. [Inspection Setup and Results] Upon verification with the samples provided, it was possible to distinguish the presence or absence of blur. Taking images slightly diagonally rather than directly from the side showed better differences in appearance due to the presence of blur. We used 13 images as training data, framed the areas we wanted to inspect, and labeled all relevant areas of each image as "Blur Present" or "No Blur." We executed approximately 500 steps of learning and set it up so that it would be marked as a failure when a "No Blur" label was found.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Detection of Screw Marks

The AI image inspection software detects scratches and dents on screws!

Manufacturers dealing with various types of motors have shown interest in our AI-based image inspection software "DeepSky" since its launch. This time, it will assess scratches and dents on screws. Our inspection software has over 2,000 examples of 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 verification using the samples we received, we were able to detect scratches, allowing us to report favorable inspection results. We can respond free of charge to requests for demonstrations, web meetings, and demo unit loan services. The loan period for demo units is approximately one week, but availability is limited, so there may be delays. The image on the left shows annotations, while the image on the right shows the detection frame with a favorable assessment.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Detection of Terminal Defects

The AI image inspection software detects the condition of terminal crimping and determines it as OK/NG!

We received an inquiry from a manufacturer of automotive and construction machinery harnesses. They would like to conduct inspections using our software based on a request from the client, as they cannot confirm the state of terminal crimping through image inspection. A free preliminary evaluation was conducted. In the free sample evaluation, we first perform a simple verification using the samples or images provided, and we report the verification results. The simple verification assesses 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, and evaluating 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 conducted verification using our "DeepSky" equipped with deep learning capabilities. As a result, we were able to detect and judge each NG item. The left image shows detection frames indicating two types of abnormalities. The right image displays the number of detections that can be confirmed on the settings screen. However, in this verification, there were some instances of false judgments. Therefore, I believe it will be necessary to increase the number of verifications in the future.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Presence or Absence of Cable Ties

We will conduct an inspection of the presence or absence of cable ties using AI image inspection software!

In wire harness manufacturing, there is a process of bundling multiple harnesses together. While traditional "EasyInspector" is often used for inspecting electronic components, combining it with "DeepSky," which utilizes Deep Learning, can sometimes lead to higher quality production. 【Inspection Settings and Results】 Even with harnesses of various colors, we were able to accurately assess the bands regardless of their front or back. In the images provided this time, the large field of view made detection more challenging. We advised that taking close-up shots would improve accuracy. The numbers in the images represent the AI confidence percentage (number of recognition points). 【Software Used】 Software Used: DeepSky The current EasyInspector2 is equipped with AI capabilities and can handle inspections of defects with various colors and shapes. We will suggest software tailored to your inspection targets.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Judgment of Circuit Board Assembly

It detects good IC leads and poor solder conditions (lifting)!

We received a contact from a manufacturer that produces hardware and software for printed circuit board manufacturing and assembly. They are considering whether it is possible to perform image diagnostics to assess the quality of soldering after components are mounted on the printed circuit board and soldered. 【Inspection Settings and Results】 Based on the images provided, we were able to identify the NG (not good) areas as NG. In this verification, we used a total of 9 images: 6 images (NG1-3, OK1-3) as training data to create the model, but since we could not detect NG7-8, we added these 3 images to the training set. As a result, we were able to detect correctly, but since the occurrence of NG was fixed at the far right, further verification is needed to determine if detection is possible with other patterns.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Judgment of Injection Molded Products

Detects "scratches," "welds," and "dot debris" on metal formed products.

We received an inquiry from a manufacturer specializing in automatic control design and maintenance. They were considering conducting visual inspections for container lids made from injection-molded products, which are placed on an index table and processed at a rate of 18 pieces per minute (3 seconds per piece). They attempted to detect "scratches," "welds," and "spot debris." 【Inspection Settings and Results】 Initially, we conducted verification using images captured within the illuminated area. In the verification environment, it was possible to identify scratches, welds, and spot debris. Additionally, for weld lines specifically, an imaging method using a polarizing filter (as shown in the left diagram) proved effective. Our company offers 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. 【Software Used】 Software Used: DeepSky

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Defect Inspection of Resin Molded Products

The AI image inspection software detects defects in molded products!

There have been instances where defects such as scratches, bumps, and foreign matter contamination occur in resin-molded parts like automotive components due to processing methods, causing difficulties. 【Inspection Settings and Results】 By using the "Scratch and Bump Inspection" feature of EasyInspector, we were able to determine scratches and bumps across the entire field of view in 0.5 seconds. Two inspection frames were created for the entire area, setting them apart as "white" and "black." 【Software and Equipment Used】 Software Used: EasyInspector710 Field of View: 10 x 6 mm Minimum Size of Inspection Target: 2 mm Number of Inspection Points: 1 (entire area) Camera Resolution: 300,000 pixels Lens Focal Length: 50 mm + 10 mm Macro Ring Distance Between Lens and Product: 190 mm Lighting: Ring Lighting Distance from Lighting to Inspection Item: Not recorded The current 'EasyInspector2' color package can be used for [Scratch and Bump Detection].

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Left and Right Discrimination of Molded Products

We will perform symmetry detection of molded product shapes using AI image inspection software!

We received an inquiry from a manufacturer that produces a wide range of products, including vinyl chloride monomers, polymers, and special PVC resins, with whom we have had a business relationship for some time. They asked if our group company could distinguish the shapes of molded products (specifically, symmetrical shapes) and contacted us regarding this matter. 【Inspection Settings and Results】 We used a total of 14 images as training data, consisting of 7 images of the left side and 7 images of the right side. We enclosed the object we wanted to detect (in this case, the entire workpiece) in a frame and labeled them as "LH" and "RH" respectively (as shown in the left image). This process was carried out for all 14 training data images. In the right image, LH is correctly recognized as LH, and RH is recognized as RH. There are no issues with recognition even if the left and right are swapped. 【Software and Equipment Used】 Software Used: DeepSky Field of View: Approximately 482 x 383 mm Minimum Size of Inspection Target: 150 mm Number of Inspection Points: 1 (to check if the left and right workpieces are aligned across the entire screen) Camera Resolution: 1.3 million pixels Lens Focal Length: 8 mm Distance Between Lens and Product: Approximately 575 mm Lighting: Indoor fluorescent lights

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Judgment of Injection Molded Parts

It will determine whether four parts are properly installed in one workpiece.

This is an inquiry from a manufacturer of thermosetting and thermoplastic resin molding processing. The inspection is based on the images provided. 【Inspection Settings and Results】 The left image shows the annotation work to outline the area to be inspected. The right image shows the detection frame. There were no instances where defective products were incorrectly classified as acceptable, but there were 2 images where acceptable products were incorrectly classified as defective. Since September 2021, a data augmentation feature for training images has been implemented. By using this convenient feature, it is possible to learn from a larger number of images with variations in orientation, angle, and brightness of defects that occur only occasionally, which improves accuracy. 【Software Used】 Software Used: DeepSky Learning Version Number of Inspection Points: 4

  • image-38.png
  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Reading Text on Automotive Parts

The AI image inspection software reads the printed information such as product model and manufacturing date.

This is an inquiry from a manufacturer of automotive parts and accessories. I believe that clearly printing details such as model numbers and manufacturing dates on delivered products is a common practice across various industries. Our software includes basic functions for saving inspection results in CSV format or as images. It allows for the recording of which parts are associated with which product numbers, making it useful in various industries. 【Inspection Settings and Results】 By using the "OCRPro" feature of EasyInspector, we were able to read characters in 26 locations. The reading took 1.87 seconds. For characters, detection was possible using either the OCR function or the OCR Pro function, while for marks and logos, comparison inspection with master images was utilized. The images show differences in RGB and color tones in the "comparison with master image" settings. As for recording methods, results can be saved in CSV format or as images. Information like that in Table 2 will be recorded in CSV format.

  • image-40.png
  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Judgment of Part Counting

We will determine the counting of small parts using AI image inspection software.

At a plastic parts manufacturer, counting small products for shipping has become a burden. There were issues with errors in weight inspection. We will conduct a simple verification of counting small parts. With DeepSky, you can use advanced software that supports counting on a conveyor. It is designed to count in various operational methods. 【Inspection Settings and Results】 We conducted inspections using software called DeepSky, which utilizes AI (Deep Learning). By training the software on the areas we want to detect, it adjusts its own setting parameters and learns to recognize them. The inspection cycle is shorter with EasyInspector. However, counting work that is not placed in trays is difficult to judge, so we decided to verify it with DeepSky this time. The left image shows the annotation, and the right image shows the detection frame. There were misjudgments with work that perfectly overlapped without any gaps, but otherwise, the judgments were good. 【Software Used】 Software used: DeepSky Counting can also be done with the application specialized for counting, 'cazoetell'.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Insufficient or Excessive Solder Amount

The AI image inspection software accurately determines insufficient and excessive solder.

We received an inquiry from a manufacturer of FA control devices with whom we have had dealings in the past, regarding the determination of solder quantity. The combination of AI (deep learning) and image inspection can be beneficial even in high-level solution areas. Please consider our image inspection software, DeepSky, for efficient inspection. 【Inspection Settings and Results】 We are able to accurately determine insufficient and excessive solder, as can be confirmed through images. With our inspection software "DeepSky," you can easily set up inspections by enclosing the areas you want to evaluate and training the system. There is an increasing movement to automate visual inspections due to advancements in AI-based image evaluation technology. To successfully implement AI image inspection, it is crucial to clearly define the characteristics of defects. Please feel free to contact us regarding lighting and camera environments as well. 【Software Used】 Software Used: DeepSky

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Detection of Defects in Engine Water Pumps

Detects "dents, impressions, chip clogging, and large voids" in precision die-cast products!

Our image inspection software is being considered in various fields and industries. The combination of AI (deep learning) and image inspection can be beneficial even in high-level solution areas. We recommend efficient inspections with DeepSky. [Inspection Settings and Results] The results of the verification conducted with the samples you provided showed that it was possible to detect "dents, impressions, chips, and large holes" and determine pass or fail. This time, we used a software called DeepSky, which utilizes AI (Deep Learning) for inspection. 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 (sizes and features) of defects are expected, so it is necessary to increase the number of training images.

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Defect Detection of Water Pump in Engine (2)

Detects dents, pressure marks, and debris blockages in the engine water pump!

Metal products such as die-castings often reflect light, making inspection difficult in the past. With our inspection software DeepSky, released in 2020, it is now possible to operate even reflective metal products like die-castings with simple settings. 【Inspection Settings and Results】 By using DeepSky's inspection features, we were able to determine dents, impressions, and chip blockages in just 0.35 seconds. The image on the left shows the hole that should be present in a good product, while the image on the right is taken with the same color (white) as the good product's "hole," but it is accurately recognized as defective. The number at the top of the frame indicates the AI's confidence level (number of recognition points). 【Software and Equipment Used】 Software Used: DeepSky Learning Version Field of View: Approximately 56 x 42 mm Minimum Size of Inspection Target: 20 mm Number of Inspection Points: 1 overall Camera Resolution: 1.3 million pixels Lens Focal Length: 12 mm Distance Between Lens and Product: Approximately 150 mm Lighting: Flashlight (Chip blockage: spotlighting the processing hole)

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Counting Parts

Label the parts you want to count, set the pass/fail criteria, and make a judgment!

We receive numerous inquiries about counting parts. Recently, we developed software for conveyor counting as an advanced application of DeepSky. We proposed a method where, while inspecting and counting, if you want to count 1,000 items, you can set the conveyor to light up at 990, have the workers line up in a row, and then stop the conveyor again at 1,000. In this inquiry, we attempted a test to count 23 correct workpieces while stationary on the workbench. 【Inspection Settings and Results】 In the settings shown in the left image, the parts to be counted are labeled as "Work," while other mixed parts are labeled as "Excluded." When set up as shown in the image above, the configuration passes if there are 20 counted parts (Work). The "Rs" on the right indicates the number of recognition points to be detected, set individually. The right image displays the detection screen. 【Software and Equipment Used】 Software Used: DeepSky Field of View: 280 x 200 mm Minimum Size of Inspection Target: 2 mm Number of Inspection Points: 8 Camera Resolution: 1.3 Megapixels Lens Focal Length: 6 mm Distance Between Lens and Product: Approximately 330 mm Lighting: Indoor Fluorescent Light

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Discrimination of Metal Parts

We will determine the defects of parts of cutting equipment using AI image inspection software!

The industrial knife manufacturer focuses on high quality, precision, and functionality in the production of cutting tools for various objects, and is committed to pursuing product quality control. This time, we are verifying the judgment of defects in cutting machine parts. The current inspection method is conducted using visual checks and jigs, but there tends to be negligence during busy periods, leading to incidents that result in complaints. Since this is a common case with a variety of workpieces, we have also created a video to make it easier to visualize. Please take a look for reference. "Discovering the omission of two types of parts at the same time and stopping the conveyor" https://skylogiq.co.jp/DIY_HowTo/368 【Inspection Settings and Results】 It was possible to detect defective parts. However, due to the variety of workpieces, it is necessary to set an appropriate field of view for each size. There were also instances where defects could not be captured directly from above, necessitating angled imaging of holes, which is expected to make positioning and environmental conditions more stringent, as reported. 【Software Used】 Software used: DeepSky

  • Image Processing Software
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Appearance Inspection of Needle Packaging

We will identify the "double," "diagonal," and "vertical misalignment" of the product after the needle packaging!

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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Defect Detection of Plate-shaped Parts

The AI image inspection software detects defects such as dirt and scratches on flat parts!

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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Defects in Cast Products

Detect multiple defects in cast products! Detect and evaluate various defects with a single 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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Burrs and Black Spots on Metal Parts

The AI image inspection software detects burrs and black spots on metal parts!

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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Foreign Objects in Metal Products

Detect foreign objects in metal products with AI image inspection 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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Inspection of Precision Cast Parts

We conduct inspections of cast precision parts using AI image inspection software to detect small defects!

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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Inspection of Metal Coating

The AI image inspection software detects and identifies defects such as "scratches," "bleeding," and "spots" on metal painted products!

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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration

[AI Image Inspection Case] Detection of Spatter on Metal Products

Detects deformation caused by metal product drooping and spattering!

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
  • Visual inspection software

Added to bookmarks

Bookmarks list

Bookmark has been removed

Bookmarks list

You can't add any more bookmarks

By registering as a member, you can increase the number of bookmarks you can save and organize them with labels.

Free membership registration