Abstract
Bit-level information is useful in image coding especially in image compression. A digital image is constructed by multilevel information of bits, called as bit-plane information. For an 8-bits gray level digital image, bit-plane extraction has ability to extract 8 layers of bit-plane information. Conventional neural network-based face recognition usually used gray images as training and testing data. This paper presents a novel method of using bit-level images as input to feedforward neural network. CMU AMP Face Expression Database is used in the experiments. Experiment result showed improvement in recognition rate, false acceptance rate (FAR), false rejection rate (FRR) and half total error rate (HTER) for the proposed method. Additional improvement is proposed by introducing dummy blank images which consist of plain 0 and 1 images in the neural network training set. Experiment result showed that the final proposed method of introducing dummy blank images improve FAR by 3.5%.
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References
Turk, M.A., Pentland, A.P.: Face Recognition Using Eigenfaces. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Hawaii, pp. 586–591 (1991)
Cruz-Llanas, S., Ortega-Garcia, J., Martinez-Torrico, E., Gonzalez-Rodriguez, J.: Comparison of Feature Extraction Techniques in Automatic Face Recognition Systems for Security Application. In: IEEE 34th Annual International Carnahan Conference on Security Technology, Ottawa, pp. 40–46 (2000)
Feris, R.S., Cesar, R.M., Kruger, V.: Efficient Real-Time Face Tracking in Wavelet Subspace. In: IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, Vancouver, pp. 113–118 (2001)
Wiskott, L., Fellous, J.M., Kuiger, N., von der Malsburg, C.: Face Recognition by Elastic Bunch Graph Matching. IEEE Trans. Pattern Analysis and Machine Intelligence 19(7), 775–779 (1997)
Lao, S., Sumi, Y., Kawade, M., Tomita, F.: 3D Template Matching for Pose Invariant Face Recognition Using 3D Facial Model Built with Isoluminance Line Based Stereo Vision. In: 15th International Conference on Pattern Recognition, Barcelona, vol. 2, pp. 911–916 (2000)
Hu, Y., Jiang, D., Yan, S., Zhang, L., Zhang, H.: Automatic 3D Reconstruction for Face Recognition. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 843–848 (2004)
Bowyer, K.W., Chang, K., Flynn, P.: A Survey of Approaches to Three-Dimensional Face Recognition. In: 17th International Conference on Pattern Recognition, vol. 1, pp. 358–361 (2004)
Zhang, B., Zhang, H., Sam Ge, S.: Face Recognition by Applying Wavelet Subband Representation and Kernel Associative Memory. IEEE Transactions on Neural Networks 15(1), 166–177 (2004)
Amira, A., Farrell, P.: An Automatic Face Recognition System Based on Wavelet Transforms. In: IEEE International Symposium on Circuits and Systems 2005, vol. 6, pp. 6252–6255 (2005)
Gao, Y.S., Leung, M.K.H.: Face Recognition Using Line Edge Map. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(6), 764–779 (2002)
Rabbani, M., Melnychuck, P.W.: Conditioning Contexts for The Arithmetic Coding of Bit Planes. IEEE Trans. on Signal Processing 40(1), 232–236 (1992)
Zhang, R., Yu, R., Sun, Q., Wong, W.: A New Bit-Plane Entropy Coder for Scalable Image Coding. In: IEEE International Conference on Multimedia and Expo 2005, pp. 237–240 (2005)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, Inc., New Jersey (2002)
Fausett, L.: Fundamentals of Neural Networks: Architectures, Algorithms, and Applications. Prentice Hall, New Jersey (1994)
AMP Advance Multimedia Processing Lab, Face Authentication Project, http://amp.ece.cmu.edu/projects/FaceAuthentication/download.htm
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Bong, D.B.L., Ting, K.C., Wang, Y.C. (2009). Novel Face Recognition Approach Using Bit-Level Information and Dummy Blank Images in Feedforward Neural Network. In: Mehnen, J., Köppen, M., Saad, A., Tiwari, A. (eds) Applications of Soft Computing. Advances in Intelligent and Soft Computing, vol 58. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89619-7_47
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DOI: https://doi.org/10.1007/978-3-540-89619-7_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89618-0
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