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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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
Online ISBN: 978-3-540-89619-7
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