한국정보처리학회:학술대회논문집 (Proceedings of the Korea Information Processing Society Conference)
- 한국정보처리학회 2010년도 춘계학술발표대회
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- Pages.377-380
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- 2010
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
지역 근처 차이를 이용한 텍스쳐 분류에 관한 연구
Texture Classification Using Local Neighbor Differences
- Saipullah, Khairul Muzzammil (Dept. of Electronic Engineering, Inha University) ;
- Peng, Shao-Hu (Dept. of Electronic Engineering, Inha University) ;
- Park, Min-Wook (Dept. of Electronic Engineering, Inha University) ;
- Kim, Deok-Hwan (Dept. of Electronic Engineering, Inha University)
- 발행 : 2010.04.23
초록
This paper proposes texture descriptor for texture classification called Local Neighbor Differences (LND). LND is a high discriminating texture descriptor and also robust to illumination changes. The proposed descriptor utilizes the sign of differences between surrounding pixels in a local neighborhood. The differences of those pixels are thresholded to form an 8-bit binary codeword. The decimal values of these 8-bit code words are computed and they are called LND values. A histogram of the resulting LND values is created and used as feature to describe the texture information of an image. Experimental results, with respect to texture classification accuracies using OUTEX_TC_00001 test suite has been performed. The results show that LND outperforms LBP method, with average classification accuracies of 92.3% whereas that of local binary patterns (LBP) is 90.7%.