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 point, P has a circle, and the center of Y has an acute angle.Studies of eye movements during image recognition have shown that the line of sight is always focused on the main features of the image, that is, on the places where the curvature of the image outline is the greatest or where the direction of the outline suddenly changes, and where the amount of information is the greatest.And the scanning route of the eye is always transferred from one feature to another in turn.It can be seen that in the process of image recognition, the perceptual mechanism must exclude the input of excess information and extract key information.At the same time, there must be a mechanism in the brain responsible for integrating information, which can organize the information obtained in stages into a complete perceptual image.

In the human image recognition system, the recognition of complex images often has to be achieved through different levels of information processing.For a familiar figure, because you grasp its main features, you will recognize it as a unit, and no longer pay attention to its details.This overall unit of isolated unit material is called blocks, and each block is perceived at the same time.In the recognition of written materials, people can not only form a block of strokes or partial units of a Chinese character, but also form block units of words or words that often appear together.

Image recognition technology is an important area of artificial intelligence.In order to compile computer programs that simulate human image recognition activities, different image recognition models have been proposed.For example, template matching models.This model believes that to identify an image, there must be a memory pattern of the image in past experience, also known as a template.If the current stimulus matches the template in the brain, the image is recognized.For example, if there is a letter A, if there is an A template in the brain, the size, orientation, and shape of the letter A are exactly the same as the A template, and the letter A is recognized.Pattern recognition in image recognition is a process of automatically identifying and evaluating shapes, patterns, curves, numbers, character formats and graphics based on a large amount of information and data, based on expert experience and existing understanding, using computer and mathematical reasoning.Pattern recognition includes two stages, namely the learning stage and the implementation stage, the former is to select the characteristics of the sample and find the law of classification, and the latter is to classify and identify the unknown sample set according to the classification law.This pattern-aware template matching model is simple and straightforward, and it is easy to get practical application.But this model emphasizes that the image must be exactly in line with the template in the brain to be recognized, and in fact, people can not only recognize the image that is completely consistent with the template in the brain, but also the image that is not completely consistent with the template.For example, people can identify not only a specific letter A, but also various letters A of print, handwriting, wrong direction, and different sizes.At the same time, the number of images that people can recognize is large, and it is impossible if every image recognized has a corresponding template in the brain.

In order to solve the problem of template matching model, Gestalt psychologists proposed a prototype matching model.This model argues that what is stored in long-term memory is not the countless templates to be recognized, but some "similarities" of the image.The "similarity" abstracted from the image can be used as a prototype to examine the image to be identified.If a similar prototype can be found, the image will be recognized.This model is more suitable for neural and memory exploration than template matching models, and can also illustrate the recognition of some irregular but in some ways similar to prototype images.However, this model does not explain how people identify and process similar stimuli, and it is difficult to achieve in computer programs.Therefore, a more complex model has been proposed, that is, the "pan-magic" recognition model.