Title :
Perceptually-tuned multiscale color-texture segmentation
Author :
Chen, Junqing ; Pappas, Thrasyvoulos N. ; Mojsilovic, Aleksandra ; Rogowitz, Bernice E.
Author_Institution :
Electr. & Comput. Eng., Northwestern Univ., Evanston, IL, USA
Abstract :
We present a perceptually-tuned multiscale image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm extends a previously proposed approach to include multiple texture scales. The determination of the multiscale texture features is based on perceptual considerations. We also examine the perceptual tuning of the algorithm and how it is affected by the presence of different texture scales. The multiscale extension is necessary for segmenting higher resolution images and is particularly effective in segmenting objects shown in different perspectives. The performance of the proposed algorithm is demonstrated in the domain of photographic images.
Keywords :
feature extraction; image classification; image colour analysis; image resolution; image segmentation; image texture; image resolution; multiple texture scale; multiscale image segmentation algorithm; object segmentation; perceptual tuning; photographic image; spatially adaptive color; texture feature; Color; Content based retrieval; Focusing; Frequency; Humans; Image resolution; Image retrieval; Image segmentation; Layout; Testing;
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
Print_ISBN :
0-7803-8554-3
DOI :
10.1109/ICIP.2004.1419450