TY - GEN
T1 - Organizing WWW images based on the analysis of page layout and web link structure
AU - Cai, Deng
AU - He, Xiaofei
AU - Ma, Wei-Ying
AU - Wen, Ji-Rong
AU - Zhang, Hongjiang
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 - 2004
Y1 - 2004
N2 - Due to the rapid growth of the number of digital images on the Web, there is an increasing demand for effective and efficient method for organizing and retrieving the images available. This paper describes a method for clustering and embedding WWW images. By using a vision-based page segmentation algorithm, a web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By extracting the page-to-block, block-to-image, block-to-page relationships through link structure and page layout analysis, we construct an image graph. With the image graph model, we use techniques from spectral graph theory for image clustering and embedding. Some experimental results are given in the paper.
AB - Due to the rapid growth of the number of digital images on the Web, there is an increasing demand for effective and efficient method for organizing and retrieving the images available. This paper describes a method for clustering and embedding WWW images. By using a vision-based page segmentation algorithm, a web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By extracting the page-to-block, block-to-image, block-to-page relationships through link structure and page layout analysis, we construct an image graph. With the image graph model, we use techniques from spectral graph theory for image clustering and embedding. Some experimental results are given in the paper.
UR - https://www.scopus.com/pages/publications/11244317158
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-11244317158&origin=recordpage
U2 - 10.1109/icme.2004.1394138
DO - 10.1109/icme.2004.1394138
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0780386035
SN - 9780780386037
VL - 1
T3 - 2004 IEEE International Conference on Multimedia and Expo (ICME)
SP - 113
EP - 116
BT - 2004 IEEE International Conference on Multimedia and Expo (ICME)
T2 - 2004 IEEE International Conference on Multimedia and Expo (ICME)
Y2 - 27 June 2004 through 30 June 2004
ER -