A novel hybrid approach of color image segmentation

Yangxing Liu, Takeshi Ikenaga, Satoshi Goto

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Color image segmentation is probably the most important task in image analysis and understanding. In this paper, we present a novel approach to segment color images by integrating region clustering result with edge detection result. In contrast to existing region-based clustering method, we do not cluster all pixels in an image at one time. We divide clustering process into two steps. First we only cluster those reliable pixels, whose colors are not affected by shadow or highlight, to get more reasonable initial clustering results. Then we cluster left unreliable pixels into classes obtained in previous step or new classes. To avoid over-segmenting an image, edge detection result and spatial information are utilized to merge some neighboring regions, a significant part of whose common boundary consists of weak edges, together as a whole. Experimental results demonstrate the efficacy of our algorithm to segment color images without any prior knowledge.

本文言語English
ホスト出版物のタイトルAPCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems
ページ1863-1866
ページ数4
DOI
出版ステータスPublished - 2006 12 1
イベントAPCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems - , Singapore
継続期間: 2006 12 42006 12 6

出版物シリーズ

名前IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS

Conference

ConferenceAPCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems
CountrySingapore
Period06/12/406/12/6

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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