Performance evaluation of Completed Local Ternary Pattern (CLTP) for face image recognition
Authors: Yee, S.Y., Rassem, T.H., Mohammed, M.F. and Makbol, N.M.
Journal: International Journal of Advanced Computer Science and Applications
Volume: 10
Issue: 4
Pages: 379-387
eISSN: 2156-5570
ISSN: 2158-107X
DOI: 10.14569/ijacsa.2019.0100446
Abstract:Feature extraction is the most important step that affects the recognition accuracy of face recognition. One of these features are the texture descriptors that are playing an important role as local features descriptor in many of the face recognition systems. Recently, many types of texture descriptors had been proposed and used for face recognition task. The Completed Local Ternary Pattern (CLTP) is one of the texture descriptors that has been proposed for texture image classification and had been tested for different image classification tasks. It proposed to overcome the Local Binary Pattern (LBP) drawbacks where the CLTP is more robust to noise as well as shown a good discriminative property than others. In this paper, a comprehensive study on the performance of the CLTP for face recognition task has been done. The aim of this study is to investigate and evaluate the CLTP performance using eight different face datasets and compared with the previous texture descriptors. In the experimental results, the CLTP had been shown good recognition rates and outperformed the other texture descriptors for this task. Several face datasets are used in this paper, such as Georgia Tech Face, Collection Facial Images, Caltech Pedestrian Faces, JAFFE, FEI, YALE, ORL, UMIST datasets.
Source: Scopus
Performance Evaluation of Completed Local Ternary Pattern (CLTP) for Face Image Recognition
Authors: Yee, S.Y., Rassem, T.H., Mohammed, M.F. and Makbol, N.M.
Journal: INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
Volume: 10
Issue: 4
Pages: 379-387
eISSN: 2156-5570
ISSN: 2158-107X
Source: Web of Science (Lite)