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    Scholars Journal of Engineering and Technology | Volume-4 | Issue-01
        Improved Fuzzy Support Vector Machine for Face Recognition
        Navin Prakash, Dr. Yashpal Singh
        
            Published:  Jan. 26, 2016 | 
             273
             233
        
        DOI:  10.36347/sjet
        Pages:  70-82
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        Abstract
        Face recognition is the most emerging research area of the pattern recognition since the early 1990s. This
paper presents a new classifier called modified fuzzy support vector machine (MFSVM) by modification in membership
function of Fuzzy Support Vector Machine using Combination of Distance Feature, Correlation. We use based on
discrete wavelet transform (DWT), discrete Cosine transform (DCT) as a combined feature extraction method and
modified fuzzy support vector machine (MFSVM) for face recognition. First the face image is decomposed by 2-D
wavelet, then the 2-dimentional DCT is applied to the low-frequency image. Then, using the DCT coefficient, face image
can be recognized using MFSVM classifier. The experiment is carried out on the ORL database the result is encouraging,
which achieves high accuracy
    

