Paper Details: Downloads: 1352
Serial Number: P1151618493
Title: Facial Gender Classification with Local Directional Pattern
Authors: N K Bansode and P K Sinha
Abstract: In this paper, a new approach for facial gender classification is presented. The human face serves as a knowledge base for useful demographic information such as gender, expression and age. We can easily identify the gender of the person, but it is difficult for the machine to recognize gender from the face image. The face is a complex three dimensional object and it is a challenging task for a machine to recognise gender due to a wide degree of variations in texture and shape of the face. The gender recognition has many applications in accessing the system in the society. The human computer system interaction according to the gender. The support vector machine classifier is used for gender classification. The experiment is carried out using Caltech, Yale, Orl and Lfw datasets. The result shows that the gender classification rate improved with the local directional pattern approach with the principal component analysis .
Keywords: Face Gender, local directional pattern, Princiapl Coomponets Analysis , Local Binary Pattern
Journal/Conference: International Journal of Graphics, Vision and Image Processing
Volume: 16
Issue: 2
Submission Date: 4/27/2016 12:00:00 AM
Review Date: 5/11/2016 10:28:39 AM
Publishing Date: 6/1/2016 4:45:05 PM
Article Downloads: 1352
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