Abstract
In order to promote the accuracy and practicability of resistance identifier feature recognition in the defects inspection of PCB (Printed Circuit Board), a resistance texture feature description and recognition method combining wavelet transform and Ojala’s LBP (Local Binary Pattern) operator is proposed in this paper. Firstly, wavelet analysis is adopted to decompose the original resistance image for dimension reduction. Then the approximate image is divided into several sub-blocks, and two types of sub-block LBP histogram is drawn by using two different LBP operators. Finally, we concatenated the whole histogram of every sub-blocks into histogram sequence, and the sequence is the enhanced feature vector of resistance image recognition. Experimental results show that the proposed method has a high-level recognition rate of texture feature.KeywordsWavelet TransformLBP operatorNormalizing HistogramTexture FeatureResistance Recognition
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