Wear Particles Recognition Based on Improved LBP

Guo De Wang; Zhi Sheng Jing; Guo Wei Qin; Shan Chao Tu

doi:10.4028/www.scientific.net/AMM.427-429.1874

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429Wear Particles Recognition Based on Improved LBP

Wear Particles Recognition Based on Improved LBP

Abstract:

Wear particles recognition is a key link in the process of Ferrography analysis. Different kinds of wear particles vary greatly in texture, texture feature is one of the most important feature in wear particles recognition. Local Binary Pattern (LBP) is an efficient operator for texture description. The binary sequence of traditional LBP operator is obtained by the comparison between the gray value of the neighborhood and the gray value of the center pixel of the neighborhood, the comparison is too simple to cause the loss of the texture. In this paper, an improved LBP operator is presented for texture feature extraction and it is applied to the recognition of severe sliding particles, fatigue spall particles and laminar particles. The experimental results show that our method is an effective feature extraction method and obtains better recognition accuracy compared with other methods.