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.
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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