Image preprocessing method based on local approximation gradient with application to face recognition

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• 作者：Zhaokui Li ; Yan Wang ; Chunlong Fan ; Jinrong He
• 关键词：Local approximate gradient ; Image preprocessing ; Linear discriminant analysis ; Robust dissimilarity ; Face recognition
• 刊名：Pattern Analysis and Applications
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：20
• 期：1
• 页码：101-112
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Pattern Recognition;
• 出版者：Springer London
• ISSN：1433-755X
• 卷排序：20

文摘

In order to obtain more robust face recognition results, the paper proposes an image preprocessing method based on local approximation gradient (LAG). The traditional gradient is only calculated along 0° and 90°; however, there exist many other directional gradients in an image block. To consider more directional gradients, we introduce a novel LAG operator. The LAG operator is actually calculated by integrating more directional gradients. Because of considering more directional gradients, LAG captures more edge information for each pixel of an image and finally generates an LAG image, which achieves a more robust image dissimilarity between images. An LAG image is normalized into an augmented feature vector using the “z-score” method. The dimensionality of the augmented feature vector is reduced by linear discriminant analysis to yield a low-dimensional feature vector. Experimental results show that the proposed method achieves more robust results in comparison with state-of-the-art methods in AR, Extended Yale B and CMU PIE face database.