Co-occurrence matrix and its statistical features as a new approach for face recognition

Eleyan, Dr. Alaa; DEMİREL, Hasan

Co-occurrence matrix and its statistical features as a new approach for face recognition

Alaa ELEYAN, (Lefke Avrupa Üniversitesi, Lefke, KKTC)

Hasan DEMİREL (Doğu Akdeniz Üniversitesi, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümü, KKTC)

Turkish Journal of Electrical Engineering and Computer Sciences

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Yıl: 2011 Cilt: 19 Sayı: 1 Sayfa Aralığı: 97 - 107 Metin Dili: İngilizce İndeks Tarihi: 29-07-2022

Co-occurrence matrix and its statistical features as a new approach for face recognition

Öz:

In this paper, a new face recognition technique is introduced based on the gray-level co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the information about relative positions of neighboring pixels of an image. We proposed two methods to extract feature vectors using GLCM for face classification. The first method extracts the well-known Haralick features from the GLCM, and the second method directly uses GLCM by converting the matrix into a vector that can be used in the classification process. The results demonstrate that the second method, which uses GLCM directly, is superior to the first method that uses the feature vector containing the statistical Haralick features in both nearest neighbor and neural networks classifiers. The proposed GLCM based face recognition system not only outperforms well-known techniques such as principal component analysis and linear discriminant analysis, but also has comparable performance with local binary patterns and Gabor wavelets.

Anahtar Kelime:

Konular: Mühendislik, Elektrik ve Elektronik

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	Eleyan D, DEMİREL H (2011). Co-occurrence matrix and its statistical features as a new approach for face recognition. , 97 - 107.
Chicago	Eleyan Dr. Alaa,DEMİREL Hasan Co-occurrence matrix and its statistical features as a new approach for face recognition. (2011): 97 - 107.
MLA	Eleyan Dr. Alaa,DEMİREL Hasan Co-occurrence matrix and its statistical features as a new approach for face recognition. , 2011, ss.97 - 107.
AMA	Eleyan D,DEMİREL H Co-occurrence matrix and its statistical features as a new approach for face recognition. . 2011; 97 - 107.
Vancouver	Eleyan D,DEMİREL H Co-occurrence matrix and its statistical features as a new approach for face recognition. . 2011; 97 - 107.
IEEE	Eleyan D,DEMİREL H "Co-occurrence matrix and its statistical features as a new approach for face recognition." , ss.97 - 107, 2011.
ISNAD	Eleyan, Dr. Alaa - DEMİREL, Hasan. "Co-occurrence matrix and its statistical features as a new approach for face recognition". (2011), 97-107.

APA	Eleyan D, DEMİREL H (2011). Co-occurrence matrix and its statistical features as a new approach for face recognition. Turkish Journal of Electrical Engineering and Computer Sciences, 19(1), 97 - 107.
Chicago	Eleyan Dr. Alaa,DEMİREL Hasan Co-occurrence matrix and its statistical features as a new approach for face recognition. Turkish Journal of Electrical Engineering and Computer Sciences 19, no.1 (2011): 97 - 107.
MLA	Eleyan Dr. Alaa,DEMİREL Hasan Co-occurrence matrix and its statistical features as a new approach for face recognition. Turkish Journal of Electrical Engineering and Computer Sciences, vol.19, no.1, 2011, ss.97 - 107.
AMA	Eleyan D,DEMİREL H Co-occurrence matrix and its statistical features as a new approach for face recognition. Turkish Journal of Electrical Engineering and Computer Sciences. 2011; 19(1): 97 - 107.
Vancouver	Eleyan D,DEMİREL H Co-occurrence matrix and its statistical features as a new approach for face recognition. Turkish Journal of Electrical Engineering and Computer Sciences. 2011; 19(1): 97 - 107.
IEEE	Eleyan D,DEMİREL H "Co-occurrence matrix and its statistical features as a new approach for face recognition." Turkish Journal of Electrical Engineering and Computer Sciences, 19, ss.97 - 107, 2011.
ISNAD	Eleyan, Dr. Alaa - DEMİREL, Hasan. "Co-occurrence matrix and its statistical features as a new approach for face recognition". Turkish Journal of Electrical Engineering and Computer Sciences 19/1 (2011), 97-107.