DocumentCode
2458874
Title
No Grouping Left Behind: From Edges to Curve Fragments
Author
Tamrakar, Amir ; Kimia, Benjamin B.
Author_Institution
Brown Univ., Providence
fYear
2007
fDate
14-21 Oct. 2007
Firstpage
1
Lastpage
8
Abstract
We present a framework for extracting image contours based on geometric and structural consistency among edge element locations and orientations. The paper presents two contributions. First, we observe that while the traditional edge orientation operators are based on first-order derivatives, orientation as tangent of a localized curve requires third-order derivatives. We derive a numerically stable third-order edge operator and show that it outperforms current techniques. Second, we consider all discrete n-tuples of edges in a local neighborhood (7times7) and retain those that are geometrically consistent with a third-order local curve model. This results in a number of ordered discrete combinations of edges, each represented by a bundle of curves. The resulting curve bundle map is a representation of all possible local groupings from which longer contour fragments are constructed. We validate our results and show that our framework outperforms traditional approaches to contour extraction.
Keywords
edge detection; feature extraction; contour extraction; curve bundle map; curve fragments; edge element locations; edge orientation operators; edges fragments; first-order derivatives; geometric consistency; image contours; ordered discrete combinations; structural consistency; third-order edge operator; Databases; Decision making; Filters; Fingers; Histograms; Horses; Image edge detection; Object recognition; Shape; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location
Rio de Janeiro
ISSN
1550-5499
Print_ISBN
978-1-4244-1630-1
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2007.4408919
Filename
4408919
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