RAGS: region-aided geometric snake

X Xie, M Mirmehdi

Research output: Contribution to journalArticle (Academic Journal)peer-review

95 Citations (Scopus)


An enhanced, region-aided, geometric active contour that is more tolerant towards weak edges and noise in images is introduced. The proposed method integrates gradient flow forces with region constraints, composed of image region vector flow forces obtained through the diffusion of the region segmentation map. We refer to this as the Region-aided Geometric Snake or RAGS. The diffused region forces can be generated from any reliable region segmentation technique, greylevel or colour. This extra region force gives the snake a global complementary view of the boundary information within the image which, along with the local gradient flow, helps detect fuzzy boundaries and overcome noisy regions. The partial differential equation (PDE) resulting from this integration of image gradient flow and diffused region flow is implemented using a level set approach. We present various examples and also evaluate and compare the performance of RAGS on weak boundaries and noisy images.
Translated title of the contributionRAGS: region-aided geometric snake
Original languageEnglish
Pages (from-to)640 - 652
Number of pages13
JournalIEEE Transactions on Image Processing
Volume13 (5)
Publication statusPublished - May 2004

Bibliographical note

Publisher: Institute of Electrical and Electronics Engineers


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