DocumentCode :
2097331
Title :
Hybrid Image Segmentation Using RPCCL Clustering and Region Merging
Author :
Li, Xinhui ; Shen, Runping ; Chen, Renxi
Author_Institution :
Sch. of Remote Sensing, Nanjing Univ. of Inf. & Sci. Technol., Nanjing, China
fYear :
2011
fDate :
17-18 Sept. 2011
Firstpage :
49
Lastpage :
53
Abstract :
Image segmentation is very important to image analysis and satisfying methods are still unfounded. In this paper, we propose a new hybrid segmentation approach based on rival penalized controlled competitive learning (RPCCL) and region merging scheme. In the first, we performed median filtering on input image, and then selected initial color centers by using color quantization technique. During the RPCCL clustering, we merged some close centers to reduce classes. In the end, small regions were merged to produce the final segmentation results. Compared to original RPCCL, our method can overcome over-segmentation and obtain better results.
Keywords :
data compression; image coding; image colour analysis; image segmentation; learning (artificial intelligence); pattern clustering; RPCCL clustering; color centers; color quantization technique; hybrid image segmentation; image analysis; region merging scheme; rival penalized controlled competitive learning; Clustering algorithms; Color; Educational institutions; Image color analysis; Image segmentation; Merging; Quantization; Clustering; RPCCL; Region Merging; Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Internet Computing & Information Services (ICICIS), 2011 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-1561-7
Type :
conf
DOI :
10.1109/ICICIS.2011.19
Filename :
6063190
Link To Document :
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