Computer Science ›› 2017, Vol. 44 ›› Issue (1): 303-307.doi: 10.11896/j.issn.1002-137X.2017.01.056

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Improved HOG Face Feature Extraction Algorithm Based on Haar Characteristics

JIANG Zheng and CHENG Chun-ling   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Most of existing feature extraction algorithms are prone to be influenced by external factors such as illumination,which can lead to the decrease of face recognition rate.The robustness of histogram of oriented gradient (HOG) can solve the problem that brought by illumination on face recognition rate.However,when calculating the gradient direction and amplitude of pixels,the traditional HOG algorithm considers only the impact of the four pixels situated in horizontal and vertical direction.The gradient direction and amplitude of pixels may become unstable when the external environment changes.Thus,we proposed an improved HOG face feature extraction algorithm based on Haar characteris-tics.When calculating the gradient direction and amplitude,we considered the influence of 8 pixels.Meanwhile,because of the simple and fast operating of Haar-like features,we inducted Haar into HOG.We showed four groups of Haar feature encoding models,which calculated the texture features of face according to the improved HOG.In our experiments we used FERET and Yale B datasets.Experiments demonstrate that,compared with existing algorithms,the proposed method has better robustness and improve the recognition rate under varying illumination conditions.On the fb,fc,dup1 and dup2 datasets,the recognition rates of the proposed method are 95.1%,80.9%,70.1% and 63.2% respectively.On the Yale B datasets,its rate is 89.1%.

Key words: Feature extraction,Face recognition,HOG,Haar,Encoding model

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