TY - JOUR ID - 107316 TI - Gait Recognition based on Measurements of Moving Human Legs Angles JO - International Journal of Engineering JA - IJE LA - en SN - 1025-2495 AU - Shaban Al-Ani, M. AU - Mohammadi, M. AU - AlyanNezhadi, M. M. AD - University of Human Development, College of Science and Technology, Department of Computer Science, Sulaymaniyah, KRG, Iraq AD - Image Processing & Data Mining Lab, Shahrood University of Technology, Shahrood, Iran Y1 - 2020 PY - 2020 VL - 33 IS - 5 SP - 975 EP - 983 KW - Gait Recognition KW - Leg Angle Measurement KW - Biometric Recognition KW - Human Identification DO - 10.5829/ije.2020.33.05b.31 N2 - Biometrics plays a crucial role in security systems. Gait recognition as an aspect of behavioral biometrics deals with identifying human based on the walking. In this research, we proposed a new method to identify people according to their gait characteristics. This approach is performed via several steps; a) the video frames of a walking subject is recorded. b) each video is decomposed into eight phases, wherein each phase, there are several frames. One frame per phase is selected. c) the extracted frame is segmented to separate the subject from the background. d) the image is converted to a binary image, and the skeletonization is applied to obtain the silhouette of the image. e) the fast Fourier transform is applied to each frame, and several statistical features are calculated. The average of the statistical measures for eight frames of a video is computed as a feature vector for the subject. Finally, the correlation is used to identify the subject based on the feature vector. The accuracy of 100% is achieved for the recognition of the subjects in the CASIA dataset. UR - https://www.ije.ir/article_107316.html L1 - https://www.ije.ir/article_107316_c93cd7716eeb87231f30a966685d1a62.pdf ER -