NDLI: An efficient parameterless quadrilateral-based image segmentation method

Content Provider	IEEE Xplore Digital Library
Author	Chung, R.H.Y. Yung, N.H.C. Cheung, P.Y.S.
Copyright Year	1979
Abstract	This paper proposes a general quadrilateral-based framework for image segmentation, in which quadrilaterals are first constructed from an edge map, where neighboring quadrilaterals with similar features of interest are then merged together to form regions. Under the proposed framework, the quadrilaterals enable the elimination of local variations and unnecessary details for merging from which each segmented region is accurately and completely described by a set of quadrilaterals. To illustrate the effectiveness of the proposed framework, we derived an efficient and high-performance parameterless quadrilateral-based segmentation algorithm from the framework. The proposed algorithm shows that the regions obtained under the framework are segmented into multiple levels of quadrilaterals that accurately represent the regions without severely over or undersegmenting them. When evaluated objectively and subjectively, the proposed algorithm performs better than three other segmentation techniques, namely, seeded region growing, k-means clustering and constrained gravitational clustering, and offers an efficient description of the segmented objects conducive to content-based applications.
Sponsorship	IEEE Computer Society
Page Count	13
File Size	2238312
Starting Page	1446
Ending Page	1458
File Format	PDF
ISSN	01628828
Volume Number	27
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image analysis Clustering algorithms Application software Partitioning algorithms Merging Performance evaluation Image edge detection Image recognition Layout quadrilateral-based segmentation. Index Terms- Approximate methods object representations region growing
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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