FQ2-CH15100N-M

Due to market price fluctuations, if you need to purchase or consult the price. You can contact us or emial to us:   sales@allicdata.com

FQ2-CH15100N-M camera is a high-precision recording device that is commonly used in the field of machine vision. It is designed for integration into application systems, boasting superior performance and quality. This type of camera is equipped with a 1.3 Megapixel CMOS image sensor, providing the highest resolution of 1288 x 976 pixels.

The FQ2-CH15100N-M camera is ideal for machine vision applications such as intelligent surveillance, intelligent monitoring and recording, inspection, sorting and tracking in intelligent robots. It can capture high-quality images with a wide dynamic range, low noise and excellent color fidelity.

The camera provides full-resolution images with an exposure time of 13 μs, and an adjustable frame rate from 15 fps to 76 fps. It features Aptina\'s unique advanced pixel architecture and back-side illumination (BSI) technology that allows excellent performance in low-light applications. The camera\'s low power consumption also allows for integration into robots and smart devices.

The FQ2-CH15100N-M camera\'s working principle is based on the use of Near-Infrared (NIR) light to illuminate objects. Objects are illuminated using NIR light, which is invisible to the human eye but can be detected by the camera. The camera then captures the reflected NIR light, which is then converted into a visible image.

The FQ2-CH15100N-M camera\'s working principle is based on the use of Near-Infrared (NIR) light to illuminate objects, which is then converted into a visible image and captured by the camera. This camera provides excellent performance with its highly advanced pixel architecture and back-side illumination technology, allowing it to receive high-quality images with a wide dynamic range, low noise and excellent color fidelity. It also has a fast frame rate of up to 76 fps and low power consumption, making it suitable for applications in the field of machine vision.

The specific data is subject to PDF, and the above content is for reference