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《Infrared Technology》 2014-10
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Document Image Classification Based on Improved Local Binary Patterns

ZHANG Min;School of Surveying & Land Information Engineering, Henan Polytechnic University;  
Based on the analysis of the methods to reduce the dimensions of the local binary pattern(LBP), a new operator called the orthogonal combination of local binary number(denoted as OC-LBN) is proposed for document image classification. Firstly, the local neighborhood is divided into different 4-orthogonal-neighbors, and the binary number of "1" in each 4-orthogonal-neighbor is used as its feature. Then, the features of all the 4-orthogonal-neighbor are combined together as region description. Experimental results obtained from texture, forward-Looking infrared and document image databases demonstrate that the proposed method can get the best performance of the methods mentioned in the paper.
【Fund】: 河南省国际合作项目 编号:134300510057
【CateGory Index】: TP391.41
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