A novel LBP method for invariant texture classification

Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

KBEI02_062

تاریخ نمایه سازی: 5 بهمن 1395

Abstract:

Texture classification is a basic task in many applications of machine vision and image processing. Linear Binary Pattern (LBP) methods are among the important categories of invariant texture classification methods. Moreover, Discrete Wavelet Transform (DWT) methods are the other groups of texture classification methods, which attract much attention. LBP features just consider the spatial information of the texture; therefore, this paper proposes a proper combination of the DWT and LBP methods in which we try to improve the ability of LBP methods using multi-resolution analysis. The final results show that the proposed method finely improves the classification rate of the previous and well-known LBP methods for invariant texture classification.

Authors

Ali Ahmadvand

School of Computer Engineering Iran University of Science and Technology Tehran, Iran

Mohammd Taghi Hajiali

Department of Industrial Engineering Iran University of Science and Technology Tehran, Iran

Rahim Ahmadvand

School of Allied Medical Science Iran University of Medical Sciences Tehran, Iran

Mohammad Reza Mosavi

Department of Electrical Engineering Iran University of Science and Technology Tehran, Iran