Similarity discrimination system based on five sense organs of human face

Abstract

The invention provides a similarity discrimination system based on the five sense organs of a human face. An initialization module is used for establishing an initial human face image model. A five-sense-organ positioning module is used for respectively acquiring the positions of five sense organs in the human face region of a plurality of to-be-detected human face images, dividing and extracting the region of each sense organ in the human face region. A feature extraction module is used for obtaining the similarity information of each sense organ in the human face region of the to-be-detected human face images so as to form five-sense-organ feature vectors. A judging module is used for comparing the five-sense-organ feature vectors of a to-be-detected human face with five-sense-organ feature vectors of already known human faces so as to obtain the similarity of the to-be-detected human face. Based on the system, the face features of people are basically classified through judging the similarity of the five sense organs of a human face. Meanwhile, the accurate and detailed analysis and comparison for face features is conducted. As a result, the similarity degree between the sense organs of different people or between the sense organs of people in different images can be provided for users. Furthermore, the system comprehensively embodies the similarity degree between human faces, and improves the human face analysis accuracy and the human face analysis comprehensiveness.

Description

technical field [0001] The invention belongs to the field of face recognition, in particular to a similarity discrimination system based on facial features. Background technique [0002] With the development of modern technology, digital image technology has shown its superiority. As a branch of computer, its role is not only in the field of simple image processing, but has been widely used in many fields, especially in the field of face recognition. Face analysis is widely used in daily life. People who pay more attention to appearance will care about which celebrity their appearance is closer to. Medical and aesthetic institutions have studied the structural proportions of facial features to the extreme. [0003] The traditional face recognition field mainly includes the following aspects: Image processing: optimize the image grayscale and contrast, which is conducive to extracting feature points, including denoising, improving contrast, etc. Face detection: Identify the...

AI Technical Summary

Problems solved by technology

This method is too general and general, lacks detailed explanation, and cannot provide users with intuitive partial comparison information, so that it is unconvincing

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