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Visual inspection software Product List and Ranking from 21 Manufacturers, Suppliers and Companies

Last Updated： Aggregation Period:Nov 12, 2025～Dec 09, 2025
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:Nov 12, 2025～Dec 09, 2025
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. 藤川伝導機 Tokyo//Industrial Machinery
  4. 4 三機 Creative Lab Aichi//robot
  5. 5 株式会社Roxy Aichi//IT/Telecommunications
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Visual inspection software Product ranking

Last Updated： Aggregation Period:Nov 12, 2025～Dec 09, 2025
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 visual inspection software "DeepSky" スカイロジック
  3. Appearance inspection software "MELSOFT VIXIO" 藤川伝導機
  4. 4 Appearance inspection software "MELSOFT VIXIO" 藤川伝導機
  5. 5 [AI Image Inspection Case] Reading Text on Nameplates スカイロジック

Visual inspection software Product List

121～135 item / All 470 items

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[AI Image Inspection Case] Inspection of Precision Cast Parts

[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

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[AI Image Inspection Case] Inspection of Metal Coating

[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

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

[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

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[AI Image Inspection Case] Screw Impact Inspection

[AI Image Inspection Case] Screw Impact Inspection

The AI image inspection software detects dents in screws.

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

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[AI Image Inspection Case] Scratch Inspection of Metal Parts

[AI Image Inspection Case] Scratch Inspection of Metal Parts

The AI image inspection software detects multiple scratches on metal parts!

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

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[AI Image Inspection Case] Detection of Defects in Precision Cast Parts

[AI Image Inspection Case] Detection of Defects in Precision Cast Parts

We will inspect and determine defects in precision cast parts using AI image inspection software!

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

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[AI Image Inspection Case] Missing Chip Capacitor

[AI Image Inspection Case] Missing Chip Capacitor

The AI image inspection software detects missing chip capacitors on the circuit board!

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

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[AI Image Inspection Case] Detection of Solder Bridges

[AI Image Inspection Case] Detection of Solder Bridges

We will inspect for the presence or absence of solder bridges using AI image inspection software!

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

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[AI Image Inspection Case] Air Conditioner Parts Presence Inspection

[AI Image Inspection Case] Air Conditioner Parts Presence Inspection

We will determine the presence or absence of seals, resin parts, and cables from a single image!

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

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[AI Image Inspection Case] OCR Reading of Circuit Boards

[AI Image Inspection Case] OCR Reading of Circuit Boards

We will perform OCR reading on the chip capacitors printed on the electronic component mounting board!

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

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[AI Image Inspection Case] Detection of Chipping on the Side of a Circuit Board

[AI Image Inspection Case] Detection of Chipping on the Side of a Circuit Board

The AI image inspection software detects missing parts on the substrate side!

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

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[AI Image Inspection Case] Counting Processed Parts

[AI Image Inspection Case] Counting Processed Parts

We will inspect for any defective items while counting the number of necessary parts!

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

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[AI Image Inspection Case] Clip Overhang

[AI Image Inspection Case] Clip Overhang

Measure the vertical dimensions of the clip and determine the pass or fail based on the overall length.

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

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[AI Image Inspection Case] Coating Amount Inspection of Coating Agents

[AI Image Inspection Case] Coating Amount Inspection of Coating Agents

We will conduct an inspection of the application amount of the coating agent using AI image inspection software.

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

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[AI Image Inspection Case] Metal Drip Inspection

[AI Image Inspection Case] Metal Drip Inspection

We will inspect metal products for "dents," "unwelded areas," and "holes."

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

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