文章基本信息

标题：ILLUMINATION NORMALIZATION USING LOCAL GRAPH STRUCTURE
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作者：HOUSAM KHALIFA BASHIER ; LIEW TZE HUI ; MOHD FIKRI AZLI ABDULLAH 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2014
卷号：59
期号：3
出版社：Journal of Theoretical and Applied
摘要：The problem associated with Illumination variation is one of the major problems in image processing, pattern recognition, medical image, etc; hence there is a need to handle and deal with such variations. This paper presents a novel and efficient algorithm for images illumination correction call local graph structure (LGS). LGS features are derived from a general definition of texture in a local graph neighborhood. The idea of LGS comes from a dominating set for a graph of the image. The experiments results on ORL face database images demonstrated the effectiveness of the proposed method. The new LGS method can be stabilized more quickly and obtain higher correct rate compare to local binary pattern (LBP). Finally, LGS is simple and can be easily applied in many fields, such as image processing, pattern recognition, medical image as preprocessing
关键词：Local Graph Structure; Feature Extraction; Pattern Recognition; Illumination Variation; Local Binary Pattern; Texture Classification.