Research progress of optical vision sensor technology

Optical vision sensor technology is a kind of TPS3619-33DGKR sensor technology based on optical principle and image processing technology, which is widely used in machine vision, automatic control, intelligent transportation, unmanned driving and other fields. With the development of computer vision and deep learning algorithms, optical vision sensor technology has been rapidly developed, and has made important research progress in various fields.

First，principle and classification of optical vision sensor technology

Optical vision sensor technology is a technology that uses the propagation and reflection characteristics of light to realize object recognition and measurement. According to the different measurement targets, optical vision sensors can be divided into two types: contact and non-contact. Contact optical sensors are measured by the contact between the object and the sensor, common applications include photoelectric encoders, contact scanners and so on. Non-contact optical sensors are measured by reflection and propagation of light, and common applications include cameras, lidar, and so on.

Second，the application field of optical vision sensor technology

Optical vision sensor technology is widely used in various fields. In the field of machine vision, optical vision sensors can be used for tasks such as object recognition, positioning and tracking, and common applications include parts inspection on automated production lines, robot visual navigation, and so on. In the field of intelligent transportation, optical vision sensors can be used for tasks such as vehicle identification, lane detection and traffic flow statistics, and common applications include intelligent traffic signal control systems and intelligent parking systems. In the field of unmanned driving, optical vision sensors are one of the key technologies to achieve autonomous driving and can be used for tasks such as environment perception, obstacle detection and path planning.

Third，research progress of optical vision sensor technology

1, high-resolution image sensor: With the continuous development of cameras and image processing technology, high-resolution image sensors can provide clearer and finer image information, thereby improving the accuracy of object recognition and measurement.

2, Deep learning algorithms: Deep learning algorithms have made great progress in the field of computer vision, and can achieve tasks such as object recognition, target tracking, and scene understanding. Combined with optical vision sensor technology, a higher level of image processing and analysis can be achieved.

3, multi-spectral imaging technology: multi-spectral imaging technology can obtain image information of multiple bands at the same time, which is used to realize the identification and analysis of object materials. For example, in the field of agriculture, multispectral imaging technology can be used to detect the growth state and disease of crops.

4, optical sensor network: Optical sensor network is a distributed sensor network, can achieve a wide range of target detection and monitoring. By fusing and analyzing data from multiple optical sensors, it is possible to track and analyze targets in complex environments.

5, Lidar technology: Lidar technology is a sensor technology based on the principle of laser beam ranging, which can achieve high-precision distance measurement of the target. Combined with optical vision sensor technology, 3D reconstruction and shape recognition of the object can be realized.

Number four. challenges and development directions of optical vision sensor technology

Although optical vision sensor technology has made important research advances, it still faces some challenges. First, the resolution and sensitivity of the sensor need to be further improved to obtain higher quality image information. Second, the cost and power consumption of sensors need to be further reduced to improve their viability in large-scale applications. In addition, optical vision sensor technology also needs to solve the problem of target detection and tracking in complex environments.

Future development directions include: further improving the resolution and sensitivity of image sensors; Develop more advanced image processing and analysis algorithms; Research on new optical sensor materials and structures to improve sensor performance and reliability; Explore new optical sensor networks and liDAR technologies to enable perception and understanding of complex environments.

In short, optical vision sensor technology has important application prospects in the fields of machine vision, automatic control, intelligent transportation and unmanned driving. With the continuous development of computer vision and deep learning algorithms, optical vision sensor technology will be further improved and developed, providing more possibilities for applications in various fields.