A novel multiscale image segmentation algorithm is presented, which is based on the dominant color and homogeneous texture features (HTF) that are adopted in the MPEG-7 standard. These features are efficiently combined to perform the automatic segmentation. First, the image is roughly segmented into textured and nontextured regions using Gabor decomposition. A multiscale segmentation is then applied to the resulting regions, according to the local texture feature. Finally, a precise boundary refinement procedure is employed to accurately determine the boundaries between textured and nontextured regions. A novel region merging algorithm is introduced with a simple and effective segment classification by using HTF to deal with the over-segmentation problem. Experiments show that our algorithm provides an improved performance compared with JSEG and a watershed algorithm.
|Translated title of the contribution||Multiscale color-texture image segmentation with adaptive region merging|
|Title of host publication||2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI, USA|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||1213 - 1216|
|Number of pages||4|
|ISBN (Print)||1424407281, 1424407273|
|Publication status||Published - Apr 2007|
|Event||2007 IEEE International Conference on Acoustics, Speech, and Signal Processing - Hawaii Convention Center, Honolulu, HI, United States|
Duration: 15 Apr 2007 → 20 Apr 2007
|Conference||2007 IEEE International Conference on Acoustics, Speech, and Signal Processing|
|Abbreviated title||ICASSP '07|
|Period||15/04/07 → 20/04/07|
Bibliographical noteRose publication type: Conference contribution
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- multiscale segmentation
- dominant colour
- adaptive region merging
- homogeneous texture