Abstract: The new color local texture features that means Color Local Gabor Wavelets (CLGWs) and Color Local Binary Pattern (CLBP), for the purpose of Face Recognition (FR). This method is able to provide excellent recognition rates for face images taken under severe variation in illumination as well as for small (low) resolution face images. In addition, the feasibility of color local texture features has been successfully demonstrated by making comparisons with other state of the art color FR Methods. Color Local Texture Method do not easy to recognize the face and if variation in face means do not get proper results. Linear Discriminant Analysis (LDA) is commonly used technique for data classification and dimensionality reduction. LDA approach overcomes the above problem. The objective of LDA is to perform dimensionality reduction while preserving as much of the class discriminatory information as possible. Linear discriminant analysis is also known as Fishers discriminant analysis and it searches for those vectors in the underlying space that best discriminate among classes.
V. Arathy and P. Srinivasa Babu, 2014. Effective Face Recognition Through Color Local Texture Features. Asian Journal of Information Technology, 13: 170-174.