TY - GEN
T1 - Study on texture feature extraction in region-based image retrieval system
AU - Liu, Ying
AU - Zhang, Dengsheng
AU - Lu, Guojun
AU - Ma, Wei-Ying
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2006
Y1 - 2006
N2 - Texture is an important feature to describe images. Though his of work has been done for efficient texture feature extraction from rectangular images, no much effort has been made in texture feature extraction from arbitrary-shaped regions in region-based image retrieval (RBIR) system. In this paper, we present an efficient texture feature extraction algorithm for arbitrary-shaped regions. This algorithm first extends an arbitrary-shaped region into a rectangular area onto which block transformation can he applied. Based on the Projection-Onto-Convex-Sets (POCS) theory, a set of coefficients best describing the original region are finally obtained, from which texture feature of the region can be extracted. Via intensive experiments, we select a set of parameters proper for image retrieval purpose. Experimental results on real-world image database demonstrate the effectiveness of the proposed algorithm for image retrieval purpose. ©2006 IEEE.
AB - Texture is an important feature to describe images. Though his of work has been done for efficient texture feature extraction from rectangular images, no much effort has been made in texture feature extraction from arbitrary-shaped regions in region-based image retrieval (RBIR) system. In this paper, we present an efficient texture feature extraction algorithm for arbitrary-shaped regions. This algorithm first extends an arbitrary-shaped region into a rectangular area onto which block transformation can he applied. Based on the Projection-Onto-Convex-Sets (POCS) theory, a set of coefficients best describing the original region are finally obtained, from which texture feature of the region can be extracted. Via intensive experiments, we select a set of parameters proper for image retrieval purpose. Experimental results on real-world image database demonstrate the effectiveness of the proposed algorithm for image retrieval purpose. ©2006 IEEE.
UR - https://www.scopus.com/pages/publications/34047247372
UR - https://www.scopus.com/pages/publications/34047247372#tab=impact
U2 - 10.1109/mmmc.2006.1651329
DO - 10.1109/mmmc.2006.1651329
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 1424400287
SN - 9781424400287
VL - 2006
T3 - MMM2006: 12th International Multi-Media Modelling Conference - Proceedings
SP - 264
EP - 271
BT - MMM2006: 12th International Multi-Media Modelling Conference - Proceedings
T2 - MMM2006: 12th International Multi-Media Modelling Conference
Y2 - 4 January 2006 through 6 January 2006
ER -