The intelligent vision sensor is easy to learn, use, maintain, and install. It is becoming a reliable and effective visual detection system. Technology for it is developing rapidly. The front-end vision method is often used to extract features from images. However, how to improve the accuracy of the visual odometer is still challenging. Among the vision sensors, three-dimensional (3D) vision sensors include passive and active sensors. The passive sensor obtains the target image by taking pictures through the camera. The active sensor projects the light image to the target through the sensor, thus receives the return signal and measures the distance.

According to the image of the target object, the contour shape of the target object is obtained to calculate its position information, and then the information is standardized and transmitted to the robot control system. The automatic calculation of the position information of the object is an important part of 3D vision technology. 3D image technology needs to be further applied in industrial control and auto navigation. Vision sensor is not a piece of independent machine equipment. It is often installed on various other machines to play a role. Its main function is to collect all kinds of visual information and then transmit the information to the machine equipment that needs it. At present, based on the two-dimensional material heterojunction, important progress has been made in the field of reconfigurable brain-like visual sensors. Two-dimensional materials are expected to become important basic electronic materials in the post-Moore era. Research development in the field also allows people to stack and integrate atomic layer materials in a “Lego-like” way.

The aim of this Special Issue is to focus on the optimization of feature extraction, edge detection, denoising, and other technologies in image analysis. Moreover, we encourage submissions that discuss brain-like vision sensors which have the function of simultaneous information detection and processing. We welcome original research and review articles discussing the state of the art.

Potential topics include but are not limited to the following:

• Image key frame extraction in vision sensing technology
• Image information coding in visual sensing technology
• Image scale-invariant feature transform (SIFT) feature point extraction of vision sensor
• Image and digital sensors in intelligent vision sensing technology
• Edge detection of digital image of vision sensor
• High-speed processing of digital image of vision sensor
• Image denoising learning of vision sensors
• Image colour processing of vision sensor
• Image antinoise self-coding of 3D vision image sensor
• Image acquisition unit of vision sensor
• Semantic information detection of vision sensor
• Retina and retinal morphological devices
• Optical response of vertical heterojunction devices
• Sensor neural networks based on Van der Waals heterojunction visual morphology