Abstract: Gait analysis is the systematic study of animal locomotion, more specifically the study of human motion, using the eye and the brain of observers, augmented by instrumentation for measuring body movements, body mechanics, and the activity of the muscles. Gait analysis is used to assess, plan, and treat individuals with conditions affecting their ability to walk. Human identification using Gait is method to identify an individual by the way he walk or manner of moving on foot. Gait recognition is a type of biometric recognition and related to the behavioral characteristics of biometric recognition. Gait offers ability of distance recognition or at low resolution. This project aims to recognize an individual using his gait features. However the majority of current approaches are model free which is simple and fast but we will use model based approach for feature extraction and for matching of parameters with database sequences. The Feature Mapping and Extraction from input image is the major task to work efficiently. The input image has been categorize horizontally, vertically and diagonally with tracking of the boundaries of human motion using Color formatting to identify the boundaries of the moving objects. Then the input image has been provided to the algorithm to classify the image and identify from the dataset. It shows the accuracy and shows the matching dataset.
Keywords: Image Processing, GAIT, Computer Vision.