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Meena, K.
- Local Texture Description Framework for Texture Based Face Recognition
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Authors
Affiliations
1 Department of Computer Applications, St. Xavier’s Catholic College of Engineering, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
3 Department of Electronics and Communication Engineering, J. P. College of Engineering, IN
1 Department of Computer Applications, St. Xavier’s Catholic College of Engineering, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
3 Department of Electronics and Communication Engineering, J. P. College of Engineering, IN
Source
ICTACT Journal on Image and Video Processing, Vol 4, No 3 (2014), Pagination: 773-784Abstract
Texture descriptors have an important role in recognizing face images. However, almost all the existing local texture descriptors use nearest neighbors to encode a texture pattern around a pixel. But in face images, most of the pixels have similar characteristics with that of its nearest neighbors because the skin covers large area in a face and the skin tone at neighboring regions are same. Therefore this paper presents a general framework called Local Texture Description Framework that uses only eight pixels which are at certain distance apart either circular or elliptical from the referenced pixel. Local texture description can be done using the foundation of any existing local texture descriptors. In this paper, the performance of the proposed framework is verified with three existing local texture descriptors Local Binary Pattern (LBP), Local Texture Pattern (LTP) and Local Tetra Patterns (LTrPs) for the five issues viz. facial expression, partial occlusion, illumination variation, pose variation and general recognition. Five benchmark databases JAFFE, Essex, Indian faces, AT & T and Georgia Tech are used for the experiments. Experimental results demonstrate that even with less number of patterns, the proposed framework could achieve higher recognition accuracy than that of their base models.Keywords
Face Recognition, Local Texture Description Framework, Nearest Neighborhood Classification, Chi-Square Distance Metric.- A Combined Approach Using Textural and Geometrical Features for Face Recognition
Abstract Views :293 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
2 Department of Computer Applications, St. Xavier’s Catholic College of Engineering, IN
3 Department of Computer Science and Engineering, Sardar Raja College of Engineering, IN
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
2 Department of Computer Applications, St. Xavier’s Catholic College of Engineering, IN
3 Department of Computer Science and Engineering, Sardar Raja College of Engineering, IN
Source
ICTACT Journal on Image and Video Processing, Vol 3, No 4 (2013), Pagination: 605-611Abstract
Texture feature plays a predominant role in recognizing face images. However different persons can have similar texture features that may degrade the system performance. Hence in this paper, the problem of face similarity is addressed by proposing a solution which combines textural and geometrical features. An algorithm is proposed to combine these two features. Five texture descriptors and few geometrical features are considered to validate the proposed system. Performance evaluations of these features are carried out independently and jointly for three different issues such as expression variation, illumination variation and partial occlusion with objects. It is observed that the combination of textural and geometrical features enhance the accuracy of face recognition. Experimental results on Japanese Female Facial Expression (JAFFE) and ESSEX databases indicate that the texture descriptor Local Binary Pattern achieves better recognition accuracy for all the issues considered.Keywords
Face Recognition, Texture Features, Geometric Features, Nearest Neighborhood Classification, Chi-Square Distance Metric.- An Illumination Invariant Texture Based Face Recognition
Abstract Views :169 |
PDF Views:0
Authors
Affiliations
1 Department of Electronics and Communication Engineering, J. P. College of Engineering, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
3 Department of Computer Applications, St. Xavier’s Catholic College of Engineering, IN
1 Department of Electronics and Communication Engineering, J. P. College of Engineering, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
3 Department of Computer Applications, St. Xavier’s Catholic College of Engineering, IN