FUZZY BASED IMAGE DIMENSIONALITY REDUCTION USING SHAPE PRIMITIVES FOR EFFICIENT FACE RECOGNITION

Abstract
Today face recognition capability of the human visual system plays a significant role in day to day life due to numerous important applications for automatic face recognition. One of the problems with the recent image classification and recognition approaches are they have to extract features on the entire image and on the large grey level range of the image. The present paper overcomes this by deriving an approach that reduces the dimensionality of the image using Shape primitives and reducing the grey level range by using a fuzzy logic while preserving the significant attributes of the texture. The present paper proposed an Image Dimensionality Reduction using shape Primitives (IDRSP) model for efficient face recognition. Fuzzy logic is applied on IDRSP facial model to reduce the grey level range from 0 to 4. This makes the proposed fuzzy based IDRSP (FIDRSP) model suitable to Grey level co-occurrence matrices. The proposed FIDRSP model with GLCM features are compared with existing face recognition algorithm. The results indicate the efficacy of the proposed method.

Authors
P. Chandra Sekhar Reddy1, B. Eswara Reddy2, V. Vijaya Kumar3
Nalla Narasimha Reddy Education Society’s Group of Institutions, India1, JNTUA College of Engineering, India2, Anurag Group of Institutions, India3

Keywords
GLCM Features, Preprocessing, Grey Level Range, Significant Image Features, Dimensionality Reduction
Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 4 , Issue: 2 )
Date of Publication :
November 2013

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