Human Identification using GAIT Recognition Technique with PAL and PAL entropy, SVM And k-means with LDA

Gait recognition is one kind of biometric technology that can be used to monitor people without their cooperation. The controlled environments such as banks; military installations and even airports need to be able to quickly detect threats and provide differing levels of access to different user groups. The Gait shows a particular way or manner of moving on foot and gait recognition is the process of identifying an individual by the manner in which they walk. And Gait is less unobtrusive biometric; which offers the possibility to identify people at a distance; without any interaction or co-operation from the subject; this is the property which makes it so attractive [2]. This paper proposed new method for gait recognition. In this, firstly binary silhouette of a walking person is detected from each frame of an image. Then secondly, the features from each frame are extracted using the image processing operation. The step size length; centre of mass and cycle length are talking as key feature. In the end, SVM, K-means and LDA are used for training and testing purpose. Here, every experiments and tests are done on gait database. At last in this paper, the result shows that the better improvement from the previous result by using SVM, K-means and LDA.