GÜRÜLTÜ İÇEREN İNSAN YÜZÜ GÖRÜNTÜLERİNDE AYRIK KOSİNÜS DÖNÜŞÜMÜ - ALT BANT TABANLI YÜZ TANIMA

Bu çalışmada öz yüz ve Fisher yüz algoritmaları ile hem Ayrık Kosinüs Dönüşümü (AKD) alt bant katsayılarından hem de orijinal görüntülerden elde edilen farklı yüz alt uzaylarında yüz tanıma başarımları ölçülmüştür. Blok olarak elde edilen AKD katsayıları enerji düzeylerine göre alt bantlara sınıflandırılmış ve enerji düzeyi en yüksek dört alt bant için öz yüz ve Fisher yüz alt uzayları oluşturulmuştur. En iyi tanıma sonucu AKD DC bileşenleri ile yapılan testlerde elde edilmiştir. Görüntülere Gauss ve tuz&biber gürültüleri belirli varyans ve yoğunluklarla eklenmiş ve yüz tanıma performansları ölçülmüştür. Bu testlerde en iyi tanıma sonucu AKD yatay ve düşey orta frekans bileşenleri ile elde edilmiştir.

Anahtar Kelimeler:

Yüz Tanıma, Öz yüz, Fisher yüz, Ayrık Kosinüs Dönüşümü

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In this work, face recognition performances of eigenface and Fisherface algorithms in different face subspaces obtained from Discrete Cosine Transform (DCT) coefficients and original images were evaluated. DCT coefficients obtained in block structure were classified into subbands according to their energy levels. Eigenface and Fisherface subspaces were determined for four subbands which have the highest energy. Best recognition rate was achieved by the DC coefficients. Face recognition performances of the faces with Gaussian and salt&paper noises with different variance and intensity were tested. Best results were achieved by the horizontal and vertical medium frequency coefficient-subbands

Keywords:

Face recognition Eigenface, fisherface, discrete cosine transform, noise,

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Turk, M., Pentland, A., Eigenfaces for recognition, Journal of Cognitive Neuroscience, Vol. 3, pp. 71- 86, (1991).
Belhumeur, Peter N., Hespanha, Joao P., Kriegman, David J., Eigenfaces vs. Fisherfaces:Recognition Using Class Specific Linear Projection, IEEE Transaction On Pattern Analysis and Machine Intelligence, Vol.19, No.7, July 1997
Martinez, Aleix M., Kak, Avinash C., PCA versus LDA, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 2, February 2001 [4] Roth Alexander, Face Recognition, http://isl.ira.uka.de/mmseminar/download/2004/A_R oth-FaceRecognition.ppt, Eylül 2005.
Zhao, W., Chellappa, R., Discriminant Analysis of Principal Components for Face Recognition
Koch E. and Zhao J. 1995. “Towards Robust and Hidden Image Copyright Labeling,” presented at Nonlinear Thessaloniki, Greece. Workshop,
Huang, J., Shi, Y.Q. and Shi, Y., 2000. “Embedding Image Watermarks in DC Trans. Circuits and Systems for Video Technol. vol. 10 (6),
Components.” IEEE pp. 974-979.
Jing, X.Y. and Zhang D., 2004. “A Face and Palmprint Discriminant DCT Feature Extraction.” IEEE Transaction On Systems, Man, And Cybernetics- Part B: Cybernetics, Vol. 34, No. 6. December 2004.
Li, B. and Ma, K., 2009. “Fisherface vs. Eigenface in the Dual-tree Complex Wavelet Domain.” 2009 Fifth International Conference on Intelligent Information Processing. Multimedia Signal
Dezhong, Z., Fayi, C. 2008. “Face Recognition based Comparison” 2008 International Symposium on Computational Intelligence and Design. Image
Abouzar, P., Yousefi, S., Setarehdan, S.K. 2007. “Hybrid WT Based-DCT Based Face Recognition” IEEE International Conference on Signal Processing and November 2007, Dubai, United Arab Emirates. 2007), 24-27
Najan, Anand, and Mrs AC Phadke. "DCT Based Face Recognition." IJEIR 1.5 (2012): 415-418.
ACHARYA, Tilak; SAHOO, Sunit Kumar. Face Recognition Using PCA and DCT Based Approach. 2013. PhD Thesis.
Lu, X. L., Yang, L., Cai, G., Mo, Z. X., & Peng, L. (2014, November). Face Recognition Based on Eigenface Image Reconstruction and Fisherface. In Advanced Materials Research (Vol. 1044, pp. 1153- 1158).