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Biometric System Using Gait Feature Analysis and Comparison Published by : International Journal of Engineering Research & Technology (IJERT) http://www.ijert.org ISSN: 2278-0181 Vol. 6 Issue 05, May - 2017 Biometric System using Gait Feature Analysis and Comparison Nishtha Gupta M. TECH (Mobile Pervasive Computing), IGDTUW, Delhi Abstract:- The world today is making rapid progress in its (health, age, size, weight, speed etc.) from its gait pattern. Gait quest to realize the dream of a creating a user friendly, analysis and recognition can form the basis of unobtrusive customer caring ambience. With every new dream comes the technologies for the detection of individuals who represent a nightmare of a security of the system lapse which may allow security threat or behave suspiciously. the misuse of the system. A major success in trying to bridge the advent of a security lapse is the use of biometrics. GAIT VERSUS OTHER BIOMETRIC TRAITS Biometric systems are becoming increasingly important, since they provide more reliable and efficient means of identity Compared to other biometrics, gait has some unique verification. Biometric gait recognition (i.e. recognizing people characteristics. The most attractive feature of gait as a biometric from the way they walk) is one of the recent attractive topics trait is its unobtrusiveness, i.e., the fact that, unlike other in biometric research. This paper presents biometric user biometrics, it can be captured at a distance and without requiring recognition based on gait. the prior consent of the observed subject. Most other biometrics Most real-life biometric systems are still unimodal. Unimodal such as fingerprints [2], face [3], hand geometry [4], iris [5], voice biometric systems perform person recognition based on a [6], and signature [7] can be captured only by physical contact or single source of biometric information. Such systems are often at a close distance from the recording probe. Gait also has the affected by some problems such as noisy sensor data, non advantage of being difficult to hide, steal, or fake. universality and spoof attacks. Multi biometrics overcomes Although the study of kinesiological parameters that define these problems. Multi biometric systems represent the fusion human gait can form a basis for identification, there are apparent of two or more unimodal biometric systems. Such systems are limitations in gait capturing that make it extremely difficult to expected to be more reliable due to the presence of multiple identify and record all parameters that affect gait. Instead, gait independent pieces of evidence. So , gait can be used alone as a recognition has to rely on a video sequence taken in controlled or biometric identification or it can be used with many other uncontrolled environments. Even if the accuracy with which we biometric trait . are able to measure certain gait parameters improves, we still do not know if the knowledge of these parameters provides adequate Keywords : Gait , Biometrics , Biometric Fusion, Matching discrimination power to enable large scale deployment of gait score, Multi biometric. recognition technologies. Moreover, studies report both that gait changes over time and that it is affected by clothes, footwear, INTRODUCTION walking surface, walking speed, and emotional condition [8]. The above facts impose limitations on the inherent accuracy of gait Biometric basically refers to the identification system based on and question its deployment as a discriminative biometric. the human characteristics . A biometric system is a pattern The ambiguity regarding the efficiency of gait-assisted recognition system that performs recognition based on some identification differentiates gait from other biometrics whose features derived from measurements of physiological or uniqueness and invariability, and therefore appropriateness for use behavioural characteristics that an individual has [1]. Biometrics in identification applications, can be more conclusively form a strong tool for authentication and security applications also determined by the study of the similarities and differences as it is difficult to hide and fake such traits. The key advantage between biometrics captured from several subjects under varying over card based or password based authentication is that conditions. This is why, at present, gait is not generally expected biometrics cannot be forgotten or lost. Biometric characteristics, to be used as a sole means of identification of individuals in large including fingerprint, facial features, iris, voice, signature, and databases; instead, it is seen as a potentially valuable component palm print , finger-knuckle, gait, finger knuckle etc. are now in a multimodal biometric system. widely used in security applications. GAIT AS MULTIBIOMETRIC COMPONENT 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 Research conducted thus far in the area of gait recognition has shown that gait can be reliable in combination with other body movements, body mechanics, and the activity of the biometrics. If we assume that palm, fingerprint, and iris methods muscles[1]. Gait analysis is used to assess, plan, and treat individuals with conditions affecting their ability to walk. It is belong to a different (obtrusive) class of biometrics, additional also commonly used in sports biomechanics to help athletes run biometrics that could be used in conjunction with gait in a multi biometric system would be face and foot pressure [9] (the latter more efficiently and to identify posture-related or movement- requiring some specialized equipment for measuring the ground related problems in people with injuries. reaction force). The study encompasses quantification (i.e., introduction and In a multi biometric system, gait and foot pressure could be used analysis of measurable parameters of gaits), as well as to narrow down the database of subjects. Subsequently, face interpretation, i.e., drawing various conclusions about the animal recognition could be used for identification of a test subject IJERTV6IS050195 www.ijert.org 377 (This work is licensed under a Creative Commons Attribution 4.0 International License.) Published by : International Journal of Engineering Research & Technology (IJERT) http://www.ijert.org ISSN: 2278-0181 Vol. 6 Issue 05, May - 2017 among the reduced set of candidate subjects. Otherwise, the three Fig3. represent the generalized process :- biometrics could be combined altogether, e.g., using the techniques described in [10]. DATABASE FIGURE 3 . GENARILIZED GAIT RECOGNITION SYTEM FIGURE 1. Several stances during a gait cycle. The silhouettes are from CMU database [11]. The parameters taken into account for the gait analysis are as RECOGNITION follows[16]: Despite the differences among walking styles, the process of walking is similar for all humans. A typical sequence of stances in Step length a gait cycle is shown in Figure 1. Stride length It is interesting to notice that in case of face recognition, there is Cadence more information in the frontal face than that in the side face. Speed Thus, recognition of the frontal face is generally easier than that of the side face. However, the situation happens to be the reverse Dynamic Base in case of gait. Usually it is easier to recognize the side view gait Progression Line than the frontal view gait due to the fact that there are more Foot Angle motion characteristics in the side view of a walking person. Up to Hip Angle the present, most reported experiments are performed on the side Squat Performance view gaits [12]. However, it is not realistic to expect only side view gait in real applications. These complementary properties of PREVIOUS WORK face and gait inspire fusion of them to get more accurate results.In previous paper ,there is fusion at feature level which follows the The study of gait as a discriminating trait was first attempted a following methodology. few decades ago from a medical/ behavioural viewpoint [14]. Later, several attempts were made to investigate the gait recognition problem from the perspective of capturing and analyzing gait signals . Most recent work investigating the appropriateness of gait as a biometric for human identification has taken place in the context of the Human ID project sponsored by the U.S. Defence Advanced Research Project Agency (DARPA). Each of the participating institutions has established its own database of sequences depicting humans walking. In previous year the gait was been used for gender classification . Psychological experiments were carried out. These experiments showed that humans can recognize gender based on gait information, and that contributions of different body components vary. The prior knowledge extracted from the psychological Figure 2. Fusion at the feature extraction level [13] experiments can be combined with an automatic method to further improve classification accuracy[17]. The proposed method which BASIC PROCESS OF GAIT RECOGNITION combines human knowledge achieves higher performance than some other methods, and is even more accurate than human It is a multistage process in which the gait of the person is observers. They also present a numerical analysis of the captured with the uniform background . Moreover, since gait contributions of different human components, which shows that recognition algorithms are not , in general, invariant to the head and hair, back, chest and thigh are more discriminative than capturing
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