Integration of kernel and DCT coefficient fuzzy matching techniques for human face recognition

• Autorzy: Bhattacharjee D. , Basu D. K. , Nasipuri M. , Kundu M.
• Języki publikacji: EN

Abstrakty

EN

In this paper we describe results of human face recognition using integration of two different fuzzy matching methods. The first method is based on the kernel matching concept. In this method the system is trained with different images of the same class. During training the presence of (55)-derived kernels are considered. Based on the presence or absence of kernels in different images of the same class one reference matrix is computed and using a fuzzy membership function on deviation of individual images from the values of reference matrix two tolerance matrices are created. In the second method using local shift invariant Discrete Cosine Transform (DCT) coefficients of images of a class, another set of reference matrix and two tolerance matrices are created in a same way as in the first method. For testing the image in a class, the values of the matching of input image with reference matrices for two different methods are calculated and classified based on their respective tolerance matrices. The final result is obtained by integrating the results from both the methods. The result of recognition is very high, where error rate is only 2.625% with false acceptance rate of 1.86%.

Słowa kluczowe

EN

human face recognition; fuzzy matching technique; kernel coefficient; DCT coefficient; discrete cosine transform

PL

rozpoznawanie twarzy ludzkiej; transformacja dyskretna

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2002
• Tom: Vol. 27, No. 2
• Strony: 61--76
• Opis fizyczny: Bibliogr. 38 poz.

Twórcy

autor

Bhattacharjee D.

autor

Basu D. K.

autor

Nasipuri M.

autor

Kundu M.

• International Institute of Information Technology, EC-96, Salt Lake, Kolkata-64, India