Image Inspection System Product List and Ranking from 17 Manufacturers, Suppliers and Companies

Last Updated：Oct 15, 2025 Aggregation Period:Sep 17, 2025～Oct 14, 2025
This ranking is based on the number of page views on our site.

Image Inspection System Manufacturer, Suppliers and Company Rankings

Last Updated：Oct 15, 2025 Aggregation Period:Sep 17, 2025～Oct 14, 2025
This ranking is based on the number of page views on our site.

山善 Osaka//Trading company/Wholesale
シーイーシー Tokyo//IT/Telecommunications
マイクロ・テクニカ Tokyo//Industrial Electrical Equipment
4 Kyoritsu Electric Corporation Shizuoka//Industrial Electrical Equipment
4 アイルミッション Kanagawa//IT/Telecommunications

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Image Inspection System Product ranking

Last Updated：Oct 15, 2025 Aggregation Period:Sep 17, 2025～Oct 14, 2025
This ranking is based on the number of page views on our site.

AI Image Inspection Device "EYEbeGenesis" 山善
AI Image Inspection System "WiseImaging" シーイーシー
Image Inspection System "Field CIS" マイクロ・テクニカ
[Work Support System] Image Poka-Yoke System Kyoritsu Electric Corporation
4 AI image inspection system & automation of water quality testing with AI アイルミッション

Image Inspection System Product List

16～21 item / All 21 items

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[Must-see for companies in Okayama Prefecture] AI Development Case - AI × Insect Damage Detection -

Detection of insect damage on leaves using AI image diagnosis.

【Features of AI × Inspection】 By pre-training AI on the elements to be recognized, it is possible to identify elements and count their quantities from images. Additionally, by training the AI on error values such as defects or breaks, it can distinguish between good and defective products. Since judgment can be made using images, it is also possible to assess error values based on temperature differences using thermal cameras.

Company：システムズナカシマ岡山支店
Price：Other

Image analysis software

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AI image inspection system & automation of water quality testing with AI

Humans can make judgments, but conventional assessment systems cannot distinguish well. We support appearance and image inspection with AI.

◆AI Image Inspection System for Various Industries: Deep Inspection◆ ~It can be judged by humans, but traditional machine and image inspection systems struggle to distinguish it. Deep Inspection excels in such cases. The more experience it gains, the higher the accuracy of its judgments, achieving extremely high-performance rapid uniformity.~ ◆Automating "Water Quality Inspection with AI" that has been done visually: Deep Inspection Liquid◆ ~AI monitors water quality inspections that have been conducted visually by humans. It enables real-time monitoring of suspended particles, bubbles, and wave conditions through a camera.~

Company：アイルミッション
Price：Other

Other operation management software
Visual Inspection Equipment
Water quality testing

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[Video Available] "Roxy AI" cleans data and improves accuracy!

Garbage In, Garbage Out. An AI that has learned from incorrect data is useless.

There is an explanatory video, so please take a look. Garbage In, Garbage Out. An AI that has learned from incorrect data is useless. In fact, AI developers say they spend 80% of their time on data preparation. Can using the latest research results and the strongest algorithms solve the problem? No. Underestimating data will render even the strongest AI a wasted treasure. If you allow difficult-to-find defects mixed in with normal images to be learned, the result will be an AI that does not detect features similar to the mixed-in defects, and that is not the AI you expected. What a human can intuitively understand, AI cannot adapt to. So, should we thoroughly check all normal images to ensure that defects are definitely not present? That would be ideal, but it requires an enormous amount of time and attention. Roxy AI considers that inappropriate data is something that will mix in. Inappropriate data that has mixed in can be removed and cleaned up. With Roxy AI, data can be cleaned throughout the entire AI learning process. We clean the data and create conditions that make it easier for the AI to learn.

Company：株式会社Roxy
Price：1 million yen-5 million yen

Visual Inspection Equipment

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Case study of an image inspection system using AI: Surface inspection process of mirrors.

Inspection accuracy improved from 60% to 99% by developing a system using AI deep learning technology, resulting in a reduction of visual inspection errors.

We would like to introduce a case where we developed a mirror surface inspection system using AI deep learning technology in the product inspection process of Murakami Kaimeido Co., Ltd., which boasts a high market share in rearview mirrors. This development has achieved an improvement in inspection accuracy (from 60% to 99%) and reduced the burden on inspectors who previously conducted visual inspections. 【Problems with the Conventional Detection System】 ■ Difficulty in quantifying image color and other attributes ■ Ambiguity in standards due to human determination of thresholds ■ Inspection accuracy of around 60% ■ Final confirmation by inspectors through visual checks 【Effects After Implementation】 ■ After full-line implementation, the number of inspection workers was reduced by 70% ■ With an eye on overseas expansion, data obtained from the automation of inspections can also be used to optimize upstream processes *For more details, please refer to the PDF document or feel free to contact us.

Company：Rist
Price：Other

Other inspection equipment and devices
Image Processing Software

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Case Study 2 of AI Image Inspection Service: Surface Inspection Process of Mirrors

We will introduce a case where our AI image inspection service improved inspection accuracy (from 60% to 97%) and reduced the burden on inspectors through visual inspection.

Rist developed a mirror surface inspection system using Deep Learning technology in the product inspection process of Murakami Kaimeido Co., Ltd., which holds the No. 1 domestic market share in rearview mirrors. This system achieved an improvement in inspection accuracy (from 60% to 97%) and reduced the burden on inspectors who previously relied on visual checks. 【Challenges】 ■ Difficulty in quantifying image color and other characteristics ■ Ambiguity in standards due to human determination of thresholds ■ The need for final visual confirmation by inspectors We have addressed these challenges with our AI image inspection system. *For more details, please download the PDF document or feel free to contact us.*

Company：Rist
Price：Other

Image Processing Software
Other inspection equipment and devices

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AI Inspection System for Agriculture "AI Hayabusa"

Reduce the burden of visual monitoring! AI instantly identifies pests and diseases.

Detecting pests and diseases in crops is a task that requires skilled techniques, time, and effort. There is always a risk of oversight and misjudgment. Mirac Optical's AI image inspection system automatically identifies pests and diseases using AI and image processing technology, achieving accurate and speedy detection. 【Application Scenarios】 - Early Detection of Pests and Diseases: By continuously monitoring the growth conditions of crops, early detection of pest and disease outbreaks can prevent the expansion of damage. - Efficiency in Pesticide Application: By accurately understanding the occurrence of pests and diseases, pesticides can be applied only where necessary, reducing unnecessary chemical use. - Improvement of Quality Control: Preventing quality deterioration due to pests and diseases allows for the production of stable quality crops. - Alleviation of Labor Shortages: Automating inspection tasks that relied on experienced personnel contributes to alleviating labor shortages. 【Effects of Implementation】 - Cost reduction through reduced monitoring time and labor costs - Prevention of damage expansion through early understanding of pest and disease occurrences - Improvement of working conditions and reduction of worker burden

Company：ミラック光学
Price：Other

Image analysis software

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