Gait identification method of bidirectional two-dimensional principal component analysis based on fuzzy decision theory

Abstract

The invention provides a gait identification method of a bidirectional two-dimensional principal component analysis based on a fuzzy decision theory, The method comprises the following steps of: firstly, pre-processing an image of a gait sequence and extracting a human body movement outline; determining a gait period and calculating an average image of a gait energy image with a whole period; constructing a training sample of an average gait energy image and dividing the training sample into N secondary image sets; calculating the best projection matrix in a row direction and an array direction of each secondary image set, and calculating a characteristic matrix of secondary images of each training sample; calculating the characteristic matrix of each secondary image by the average gait energy image to be indentified; calculating a membership degree of each training sample to the image to be indentified; and determining a classification result according to the maximum membership degree principle. According to the gait identification method disclosed by the invention, the average gait energy image is divided into a plurality of the secondary images and a coefficient matrix dimensional quantity of the average gait energy image is analyzed and reduced by the bidirectional two-dimensional principal component analysis, so that the problem that the coefficient matrix dimensional quantity of the average gait energy image in the gait identification is too high is solved, the identification efficiency is improved and the identification speed is accelerated.

Description

technical field [0001] The invention relates to an image processing technology, in particular to a bidirectional two-dimensional principal component analysis gait recognition method based on fuzzy theoretical decision-making. Background technique [0002] Gait recognition is a new type of biometric identification technology. As a biometric identification method, gait recognition is to authenticate and identify people based on their walking posture. Gait features have certain rhythmic and cyclic properties and are periodic in nature. As a habitual behavioral feature, a person's gait will not change greatly for a long time, and it has strong stability. Different from face recognition, fingerprint recognition, iris recognition and other recognition technologies, gait recognition as a biological feature has the following characteristics: easy to observe, difficult to camouflage, low requirements for system resolution, long-distance recognition, etc. Therefore, gait recognitio...

AI Technical Summary

Problems solved by technology

The average gait energy map is obtained by preprocessing technology and the obtained image is divided into multiple sub-images. The two-way two-dimensional principal component analysis is used to reduce the coefficient matrix dimension of the average gait energy sub-image, which solves the problem of average step in gait recognition. Solve the problem that the dimension of the coefficient matrix of the state energy image is too high to speed up the recognition speed

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