Image recognition technology is an important field of artificial intelligence. It refers to the technology of object recognition of image to identify the target and object of different patterns.

The development of image recognition has gone through three stages: character recognition, digital image processing and recognition, and object recognition. Image recognition, as its name implies, is to make a variety of image processing, analysis, and ultimately identify the goals we want to study. Today's image recognition refers not only to the human naked eye, but also to the use of computer technology for recognition.

Principle of Image Recognition Technology

There is no essential difference between computer image recognition technology and human image recognition in principle. Human image recognition relies on the classification of the image's own characteristics, and then recognizes the image through the characteristics of each category. When we see a picture, our brain will quickly sense that it is. Have you seen this or similar picture?

In this process, our brain recognizes the memory according to the categories that have been sorted in the memory, checks whether there is memory with the same or similar characteristics as the image, and then recognizes whether we have seen the image.

Image recognition technology may be based on the main features of the image.  Each image has its own characteristics, such as the letter A has a sharp point, P has a circle, and the center of Y has an acute angle. The research of eye movement in image recognition shows that the line of sight always concentrates on the main features of the image, that is, the places where the curvature of the image contour is the largest or the direction of the contour suddenly changes, and these places have the largest amount of information. And the scanning route of the eye always shifts from one feature to another in turn. Thus, in the process of image recognition, the perception mechanism must exclude the input redundant information and extract the key information. At the same time, there must be a mechanism responsible for integrating information in the brain, which can organize the information obtained in stages into a complete perceptual image.

Pattern recognition is an important part of artificial intelligence and information science. Pattern recognition refers to the process of analyzing and processing different forms of information representing things or phenomena to obtain a description, identification and classification of things or phenomena.

Image recognition technology is based on the main features of the image. Every image has its own characteristics. The research of eye movement in image recognition shows that the line of sight always concentrates on the main features of the image, that is, on the places where the curvature of the image contour is the largest or the direction of the contour suddenly changes. These places have the largest amount of information. And the scanning route of the eye always shifts from one feature to another in turn. Thus, in the process of image recognition, the perception mechanism must exclude the input redundant information and extract the key information. At the same time, there must be a mechanism responsible for integrating information in the brain, which can organize the information obtained in stages into a complete perceptual image.

The Process of Image Recognition Technology

Since computer image recognition technology and human image recognition principle are the same, their processes are also very similar. The process of image recognition technology is divided into the following steps: information acquisition, preprocessing, feature extraction and selection, classifier design and classification decision.

Information acquisition refers to the conversion of light or sound information into electrical information through sensors. That is to get the basic information of the object of study and transform it into the information that the machine can recognize by some way.

Preprocessing mainly refers to denoising, smoothing, transformation and other operations in image processing, so as to enhance the important features of the image.

Feature extraction and selection refers to the need for feature extraction and selection in pattern recognition. Simple understanding is that the images we study are various. If we want to use some method to distinguish them, we must recognize them by their own characteristics. The process of extracting these features is feature extraction.

The features obtained in feature extraction may not be useful for this recognition. At this time, we need to extract useful features, which is the feature selection. Feature extraction and selection is one of the key technologies in the process of image recognition, so understanding this step is the focus of image recognition。

What are the application of image recognition technology?

Image recognition includes biological recognition, object and scene recognition and video recognition. Biometric recognition includes fingerprint, palm, eye (retina and iris), face, etc. Object and scene recognition includes signature, voice, walking gait, keyboard strokes and so on.

Image recognition is a comprehensive problem, which covers image matching, image classification, image retrieval, face detection, pedestrian detection and other technologies. It has wide application value in the fields of Internet search engine, automatic driving, medical analysis, remote sensing analysis and so on.