TY - GEN
T1 - Image retrieval based on color coherence
AU - Kim, B. Y.
AU - Kim, H. J.
AU - Jang, S. J.
N1 - Funding Information:
This work was in part supported by the Regional Research Center, Korea Science and Engineering Foundation (KOSEF), Korea.
Publisher Copyright:
© 1999 IEEE.
PY - 1999
Y1 - 1999
N2 - The color histogram is a simple method for representing and comparing images, but this approach has a drawback that it does not capture spatial image attributes. Previously, color coherence vectors based on color homogeneous regions have been introduced for image retrieval since they include some spatial information. The color histogram constructed by connected components whose size is larger than a certain number of pixels. This definition takes only the spatial size into consideration. In this paper, we present new definitions of color coherence that can include spatial information, say, distance between regions. As a result, we have three types of color coherence measures. Pixels are grouped according to (1) region size only, (2) distance only and (3) both size and distance. We apply them to actual visual image retrieval applications. For the simulation, we proposed a fast segmentation and merging method. The experimental result showed that the distance information is more effective than the size information for the image retrieval.
AB - The color histogram is a simple method for representing and comparing images, but this approach has a drawback that it does not capture spatial image attributes. Previously, color coherence vectors based on color homogeneous regions have been introduced for image retrieval since they include some spatial information. The color histogram constructed by connected components whose size is larger than a certain number of pixels. This definition takes only the spatial size into consideration. In this paper, we present new definitions of color coherence that can include spatial information, say, distance between regions. As a result, we have three types of color coherence measures. Pixels are grouped according to (1) region size only, (2) distance only and (3) both size and distance. We apply them to actual visual image retrieval applications. For the simulation, we proposed a fast segmentation and merging method. The experimental result showed that the distance information is more effective than the size information for the image retrieval.
UR - http://www.scopus.com/inward/record.url?scp=77952376535&partnerID=8YFLogxK
U2 - 10.1109/TENCON.1999.818379
DO - 10.1109/TENCON.1999.818379
M3 - Conference contribution
AN - SCOPUS:77952376535
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
SP - 178
EP - 181
BT - IEEE Region 10 Annual International Conference, Proceedings/TENCON
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1999 IEEE Region 10 Conference, TENCON 1999
Y2 - 15 September 1999 through 17 September 1999
ER -