JIPS (한국정보처리학회)
Current Result Document : 3 / 4
| 한글제목(Korean Title) |
Texture Image Retrieval Using DTCWT-SVD and Local Binary Pattern Features |
| 영문제목(English Title) |
Texture Image Retrieval Using DTCWT-SVD and Local Binary Pattern Features |
| 저자(Author) |
Dayou Jiang
Jongweon Kim
|
| 원문수록처(Citation) |
VOL 13 NO. 06 PP. 1628 ~ 1639 (2017. 12) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
The combination texture feature extraction approach for texture image retrieval is proposed in this paper. Two kinds of low level texture features were combined in the approach. One of them was extracted from singular value decomposition (SVD) based dual-tree complex wavelet transform (DTCWT) coefficients, and the other one was extracted from multi-scale local binary patterns (LBPs). The fusion features of SVD based multi-directional wavelet features and multi-scale LBP features have short dimensions of feature vector. The comparing experiments are conducted on Brodatz and Vistex datasets. According to the experimental results, the proposed method has a relatively better performance in aspect of retrieval accuracy and time complexity upon the existing methods.
|
| 키워드(Keyword) |
Dual-Tree Complex Wavelet Transform
Image Retrieval
Local Binary Pattern
SVD
Texture Feature
|
| 파일첨부 |
PDF 다운로드
|
