@inproceedings{2622944a5cd94cfeb9452fbce6c25a9c,
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 FM 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.",
keywords = "Decision fusion, Fast Marching, Shape Descriptor",
author = "Abdulkerim Capar and Muhittin Gokmen",
year = "2009",
doi = "10.1007/978-3-642-04697-1_35",
language = "English",
isbn = "3642046967",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "379--388",
booktitle = "Advanced Concepts for Intelligent Vision Systems - 11th International Conference, ACIVS 2009, Proceedings",
note = "11th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2009 ; Conference date: 28-09-2009 Through 02-10-2009",
}