The series features a floating design engineered to deliver superior image quality from MOD to infinity. In addition, they are optimized for IMX536 (546/566), IMX537 (547/566), IMX676/IMX266/IMX178 and Sony 4th Generation Pregius S sensors.

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The In-Sight® 2800 is equipped with a well-established legacy vision tools library. Many functions are available, such as distance measurement, area measurement, counting, logic operation tools, etc.

The excellent recognition power of deep learning, which enables not only OK/NG judgment but also component classification based on defect types and user-defined features, detects minute defects with high accuracy.

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Multiple inspection areas can be deployed within the field of view, and arbitrary inspection tools can be executed for each area.

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The In-Sight® 2800 vision system combines deep learning technology with traditional rule-based vision tools to solve a wide range of inspection applications. From simple presence/absence inspections to complex sorting and sorting applications, the In-Sight® 2800 makes it easy to deploy error-proof solutions. Designed for factory automation, the In-Sight® 2800 enables manufacturers of all sizes to:

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Computar Optics, a part of the CBC Group, has set the world standard for lenses by pioneering new, innovative lenses constantly that surpass the competition. With a solid foundation based on Japanese engineering and agile production facilities worldwide, Computar continues to manufacture he highest-quality optical products. With a team of experts dedicated to research and development, Computar continues to push the boundaries of lens technology, ensuring that its optics exceed the expectations of diverse industries, including machine vision, life sciences, transportation, and security.

The In-Sight® 2800 is equipped with a ViDi™ EL Classify tool that utilizes deep learning technology, enabling deep learning learning on the device and outputting highly accurate results in real time.

A modular solution of built-in illumination and lenses eliminates trial and error in choosing optical options. With just a few clicks of a button, you can decide the best configuration for your application.

Equipped with visual inspection, product type identification , and deep learning ViDi EL tools that are one rank higher, visual inspection and product type identification are possible. No need to set parameters or thresholds. ・Best class image sensor. High resolution image acquisition of 1.6 million pixels (when applicable model is selected). ・Batch inspection of multiple locations within the field of view is possible. Flexible combination of inspection tools.

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Anyway, anyone can use it easily ・The setting is completed in 3 steps. Quickly start shooting with an intuitive UI. ・No need to prepare a huge number of images. ・No GPU or programming language required. No image processing expert required. ・By switching lighting colors with multi-color lighting, it is possible to acquire the optimal image for any workpiece (optional).

September 18, 2024 – Mebane, NC - Computar®, a leading machine vision lens manufacturer, has announced the released of the full line of the MPX series. The MPX series is a 16MP, ruggedized machine vision lens series featuring a 10G anti-vibration and shock resistance - ideal for harsh inspection environments.Â

The In-Sight® 2800 is equipped with both rule-based and deep learning tools, and contributes to automation in all applications from error-proofing to inspection. In addition to using the tool alone, multiple tools can be combined to build more advanced judgment logic.

The C-mount MPX lenses are lightweight, compact, and fully compatible with 2μm pixel size or less. In addition, the MPX's focus rotation angle is five times wider than that of conventional lenses, allowing for precise focus adjustment. The full line is now available in 8mm, 12mm, 16mm, 25mm, 35mm, 50mm, and 75mm focal lengths.

The ViDi™ EL Classify tool can perform not only two-type classification such as OK/NG, but also various classifications such as product type classification, sorting, and defect type classification by recognizing the characteristics of each part classification excluding individual variations. Enables higher levels of automation.

The judgment reliability of the deep learning learning model can be visually confirmed in real time without any operation, helping to build highly reliable inspections.

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The ViDi™ EL Classify tool can be used with 5-10 images per classifier and can be trained in less than 1 minute. No programming required.