Illumination Normalization Using Local Graph Structure


Bashier, Housam Khalifa and Liew, Tze Hui and Abdullah, Mohd Fikri Azli and Yusof, Ibrahim and Sayeed, Md. Shohel and Azman, Afizan and Ibrahim, Siti Zainab (2014) Illumination Normalization Using Local Graph Structure. Journal of Theoretical and Applied Information Technology, 59 (3). pp. 543-548. ISSN 1992-8645

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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.

Item Type: Article
Uncontrolled Keywords: Local Graph Structure, Feature Extraction, Pattern Recognition, Illumination Variation, Local Binary Pattern, Texture Classification
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 13 Jan 2017 05:27
Last Modified: 13 Jan 2017 05:27


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