Segmentation of Clinical Endoscopic Image Based on Homogeneity and Hue
A computer-assisted endoscopic analysis is intended and facilitates the diagnosis process. Segmentation of the image is an important step and a novel approach is proposed to segment clinical endoscopic images based on homogeneity and color feature hue. In the first stage, the regions are segmented u...
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| creator | Tjoa, M P Kirshnan, S M Kugean, C Wang, P Doraiswami, R |
| description | A computer-assisted endoscopic analysis is intended and facilitates the diagnosis process. Segmentation of the image is an important step and a novel approach is proposed to segment clinical endoscopic images based on homogeneity and color feature hue. In the first stage, the regions are segmented using a peak-finding algorithm on a 2-D histogram of homogeneity and intensity values. In the second stage, histogram analysis of the color feature hue is performed to subdivide the segmented regions obtained from the first stage. The subdivisions of different segmented regions having similar CIE (L* a* b*) color measure are merged. The proposed scheme was evaluated on a database of clinical endoscopic images.
Papers from 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, October 25-28, 2001, held in Istanbul, Turkey. See also ADM001351 for entire conference on cd-rom., The original document contains color images. |
| format | Report |
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Papers from 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, October 25-28, 2001, held in Istanbul, Turkey. See also ADM001351 for entire conference on cd-rom., The original document contains color images.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CLINICAL ENDOSCOPIC IMAGE COLOR IMAGE SEGMENTATION COLORS DATA BASES DIAGNOSIS(MEDICINE) FOREIGN REPORTS HISTOGRAMS HOMOGENEITY INTENSITY MEASUREMENT Medicine and Medical Research OPTICAL IMAGES Optics REGION MERGING REGIONS SEGMENTED SINGAPORE SURGICAL INSTRUMENTS |
| title | Segmentation of Clinical Endoscopic Image Based on Homogeneity and Hue |
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