Face Recognition Based on Local Binary Pattern Auto-correlogram
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Face recognition mainly includes face feature extraction and recognition. Color is an important visual feature. Color correlogram (CC) algorithm is commonly used in the color-based image retrieval as a feature descriptor, but most of the existing methods based on CC have problems of high computational complexity and low retrieval accuracy. Aiming at this problem, this paper proposes an image retrieval algorithm based on color auto-correlogram. The new color feature vector which describes the global and spatial distribution relation among different colors is obtained in the CC feature matrix, thus reducing the computational complexity. Inter-feature normalization is applied in color auto-correlogram (CAC) to enhance the retrieval accuracy. The experimental result shows that this integrated method can reduce the computational complexity and improves real-time response speed and retrieval accuracy.
KeywordsFace recognition Local binary pattern Auto-correlogram Support vector machine
This work is supported by the Science and Technology Department Research Project of Jilin Province (No. 20190302115GX).
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