Title :
ACO contour matching: A dominant point approach.
Author :
Ruberto, Cecilia Di ; Morgera, Andrea
Author_Institution :
Dept. of Math. & Comput. Sci., Univ. of Cagliari, Cagliari, Italy
Abstract :
In computer vision research field shape matching plays a central role. A typical approach is based on the analysis of contour points of the objects. In many cases this task is faced by taking into account a contour subset made up by dominant points. This paper is based on a shape matching technique described in [1] by using dominant points as contour points set. In order to obtain better results we adopt modified shape descriptors (shape contexts) by getting rotational invariance. Experimental results demonstrate the accuracy improvement and the computational time reduction.
Keywords :
computational complexity; computer vision; image matching; optimisation; ACO contour matching; accuracy improvement; ant colony optimization; computational time reduction; computer vision research field; contour points set; contour subset; dominant point approach; modified shape descriptors; rotational invariance; shape contexts; shape matching technique; Accuracy; Approximation algorithms; Approximation methods; Context; Genetic algorithms; Pattern recognition; Shape;
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
DOI :
10.1109/CISP.2011.6100471
