Chunhui Deng
ABSTRACT
In1 this paper we proposed a new face detection process and a new texture-based detection algorithm----binary texture extraction algorithm for image preprocessing. This algorithm is applicable to different lighting, different skin colors and complex background. Furthermore, we invented a rough face inspection method called "reduction" according to the principles of the image morphology. Finally, by integrating the algorithm with the mainstream face detection methods, such as BP (Back Propagation) neural network, Gabor and Adaboost, we demonstrated the applicability and robustness of the binary texture extraction algorithm through a set of Matlab experiments containing a variety of lighting environments and different skin colors test library.
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Digital Library
- S. Cao, Z. Yu, X. Lin, L. Jiang, and D. Zhao. 2018. A Novel BP Neural Network Based System for Face Detection. IT Convergence and Security 2017, K.J. Kim et al. (Eds.). Lecture Notes in Electrical Engineering, Vol.449. Springer Nature Singapore Pte Ltd., 137--146.Google Scholar
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- P. Viola and M. J. Jones. 2004. Robust Real-time Face Detection. International Journal of Computer Vision 57, 2(2004), 237--157. Google ScholarDigital Library
- Rafael C. Ganzalez and Rachard E. Woods. 2007. Digital Image Processing (2nd.ed.). Publishing House of Electronics Industry, Beijing. Google ScholarDigital Library
Index Terms
- A New Approach to Face Detection Based on Binary Texture Extraction Algorithm
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