The core breakthrough point of artificial intelligence is —— machine vision

Machine vision is a kind of technology that uses computers and cameras to imitate the human vision system for image analysis and processing. It combines knowledge in the fields of computer science, image processing, pattern recognition, and artificial intelligence to enable machines to "see" and understand images, providing an important basis for automation and intelligence in the real world.

The primary goal of machine vision is to enable computers to understand and analyze images as humans do. The image data obtained through the camera can be processed and interpreted in the computer, so as to realize automatic control, quality detection, object recognition, object tracking and other functions. It can be widely used in industrial automation, intelligent monitoring, medical diagnosis, traffic management and other fields.

The core technologies of machine vision include image acquisition, image pre-processing, feature extraction, target detection and recognition, etc. First, machine vision needs to obtain the image through devices such as cameras, and then pre-process the image, including denoising, enhancement, geometric correction, etc., to eliminate interference and noise in the image.

Next, machine vision will use the image processing and pattern recognition algorithm to extract the feature information in the image. These feature information can be the edge, texture, color, etc. Through the analysis of these features, the detection, classification and recognition of goals can be realized.

Object detection and recognition is one of the important tasks of machine vision. By training models and using machine learning algorithms, machine vision can identify and locate target objects in the image, such as faces, vehicles, product defects, and so on. This provides very valuable applications for automated production, intelligent security and intelligent transportation.

In addition, machine vision can also perform image analysis and understanding. Through the semantic segmentation, object tracking and other technologies, the understanding and interpretation of different regions and objects in the image can be realized, and then provide the basis for decision-making and control.

The development of machine vision technology benefits from the improvement of computer computing power, the improvement of sensor technology and the development of artificial intelligence technology such as deep learning. These advances have led to significant improvements in accuracy, real-time, and adaptability.

Although machine vision has achieved remarkable application results in many fields, there are still some challenges and problems. For example, complex scenes, lighting changes, occlusion and other factors may affect the performance of the machine vision system. Therefore, researchers and engineers need to continuously improve algorithms and technologies to improve the robustness and performance of machine vision systems.

In short, machine vision, as an important technology, is constantly changing the way we live and work. It combines technologies such as image processing, pattern recognition and artificial intelligence to allow machines to "see" and understand images like people. With the further development of technology, machine vision will play an important role in more fields, creating a more intelligent, convenient and efficient living environment for human beings.