Gender classification using Gabor PCA and SVM | |
| Author | Yar Zar Moe Myint |
| Call Number | AIT Caps. Proj. no.ICT-17-03 |
| Subject(s) | Image processing Gender identity Gabor transforms |
| Note | A capstone project report submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Engineering Information and Communication Technology, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Caps. Proj. ; no. ICT-17-03 |
| Abstract | Gender Classification can be used in variety of project. It can be used in security measurement, advertisement and other factors. This project is intended to use as a real-time gender classification system. In this project, I used a data-set of male and female from Lable Faces In theWild (LFW). Implement a feature extraction method called Gabor and Principle Component Analysis (PCA). Then used those features to train with Support Vector Machine (SVM). Finally with those data ,we’ll get the system to work. This project is capable of identifying male and female from camera or video file. The recognition rate is around 79%. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Caps. Proj. ; no. ICT-17-03 |
| Type | Capstone Project |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information and Communication Technology (ICT) |
| Chairperson(s) | Dailey, Matthew N.; |
| Examination Committee(s) | Mongkol Ekpanyapong; |
| Degree | Capstone Project (B.Sc.)-Asian Institute of Technology, 2017 |