Author/Authors :
TAHIR, NOORITAWATI MD Universiti Teknologi Mara (UiTM) - Faculty of Electrical Engineering, Malaysia , HUSSAIN, AINI Universiti Kebangsaan Malaysia - Faculty of Engineering - Department of Electrical, Electronic and Systems Engineering, Malaysia , ABDUL SAMAD, SALINA Universiti Kebangsaan Malaysia - Faculty of Engineering - Department of Electrical, Electronic and Systems Engineering, Malaysia , HUSAIN, HAFIZAH Universiti Kebangsaan Malaysia - Faculty of Engineering - Department of Electrical, Electronic and Systems, Malaysia
Abstract :
In this study, centroidal profile which is a model based approach is employed for human recognition task. This is done by extracting unique representation of gait features of the subject automatically and passively from static images of human or non human. To evaluate the effectiveness of the generated centroidal profile, Artificial Neural Network (RNB) is used as classifier. Results attained proven that the centroidal profile is appropriate as feature extraction to be used as feature vectors for human shape classification based on classification rate of RNB achieved specifically above 98%.
