DocumentCode :
2193132
Title :
Chapter 12: Contour Rectification and Analysis Using Circular Augmented Rotational Trajectory Algorithm
Author :
Apu, Russel A. ; Gavrilova, Marina L.
Author_Institution :
Dept. of Comput. Sci., Calgary Univ., Calgary, AB
fYear :
2008
fDate :
9-11 July 2008
Firstpage :
75
Lastpage :
81
Abstract :
This paper presents a novel circular augmented rotational trajectory (CART) algorithm to compute an R-space based shape descriptors which allow efficient shape matching, generalization and classification. The rotation invariant R-space representation can be used to detect invariant geometric features despite the presence of considerable noise and quantization errors. Moreover, the CART method is corner preserving and can detect the points of discontinuity in a noisy trajectory. Experimental analysis performed on a number of difficult or ambiguous object boundaries show that the CART method can correctly detect and represent the inherent shape and extract their geometric properties. The method´s universality, robustness and consistent performance on a variety of difficult shapes make it a power technique for contour representation and analysis.
Keywords :
computer vision; edge detection; image classification; image matching; image representation; circular augmented rotational trajectory algorithm; contour rectification; contour representation; rotation invariant R-space representation; shape matching; Algorithm design and analysis; Computer vision; Image analysis; Low pass filters; Multi-stage noise shaping; Noise shaping; Performance analysis; Robustness; Shape; Solid modeling; Computer Vision; R-Space; Shape Recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geometric Modeling and Imaging, 2008. GMAI 2008. 3rd International Conference on
Conference_Location :
London
Print_ISBN :
978-0-7695-3270-7
Type :
conf
DOI :
10.1109/GMAI.2008.10
Filename :
4568609
Link To Document :
بازگشت