Paper Info
Title
Shape Recognition by Voting on Fast Marching Iterations
Abstract
In this study, we present a Fast Marching (FM) - Shape Description integrated methodology that is capable both extracting object boundaries and recognizing shapes. A new speed formula is proposed, and the local front stopping algorithm in [1] is enhanced to freeze the active contour near real object boundaries. GBSD [2] is utilized as shape descriptor on evolving contour. Shape description process starts when a certain portion of the contour is stopped and continues with PM iterations. Shape description at each iteration is treated as a different source of shape information and they are fused to get better recognition results. This approach removes the limitation of traditional recognition systems that have only one chance for shape classification. Test results shown in this study prove that the voted decision result among these iterated contours outperforms the ordinary individual shape recognizers.
Year
DOI
Venue
2009
10.1007/978-3-642-04697-1_35
ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, PROCEEDINGS
Keywords
Field
DocType
Fast Marching,Shape Descriptor,Decision fusion
Active contour model,Computer vision,Active shape model,Voting,Pattern recognition,Computer science,Fast marching method,Topological skeleton,Artificial intelligence,Iterated function,Heat kernel signature,Shape analysis (digital geometry)
Conference
Volume
ISSN
Citations 
5807
0302-9743
0
PageRank 
References 
Authors
0.34
16
2
Name
Order
Citations
PageRank
Abdulkerim Çapar1194.28
Muhittin Gökmen213716.12