Affine invariant matching of broken boundaries based on simple genetic algorithm and contour reconstruction
PWM Tsang, WC Situ - Pattern Recognition Letters, 2010 - Elsevier
PWM Tsang, WC Situ
Pattern Recognition Letters, 2010•ElsevierViewpoint independent identification of fragmented object contours can be accomplished by
matching them against a collection of known reference models. For the class of near-planar
objects, the matching process can be posed as the search for the existence of an affine
transform between a pair of contours. Recently, it has been demonstrated that the search
process can be accomplished with the integration of a simple genetic algorithm (SGA) and a
quality migrant injection (QMI) operation. The performance is superior to prior arts based on …
matching them against a collection of known reference models. For the class of near-planar
objects, the matching process can be posed as the search for the existence of an affine
transform between a pair of contours. Recently, it has been demonstrated that the search
process can be accomplished with the integration of a simple genetic algorithm (SGA) and a
quality migrant injection (QMI) operation. The performance is superior to prior arts based on …
Viewpoint independent identification of fragmented object contours can be accomplished by matching them against a collection of known reference models. For the class of near-planar objects, the matching process can be posed as the search for the existence of an affine transform between a pair of contours. Recently, it has been demonstrated that the search process can be accomplished with the integration of a simple genetic algorithm (SGA) and a quality migrant injection (QMI) operation. The performance is superior to prior arts based on the use of SGA alone in terms of success rates and computation speed. The downside of such approach is the need of more computation time for generating quality migrants in the course of evolution. In this paper, we have proposed a solution to overcome this problem. Our method has two major contributions. The first one is a scheme which enables a closed boundary to be extracted from a set of fragmented object points, and represented as a one-dimensional (1−D) sequence. Second, we have applied SGA to determine the similarity between a pair of closed boundaries by searching the existence of three correspondence point pairs in their 1−D sequences. As a result of these two contributions, the proposed method is substantially faster than the SGA–QMI scheme, and also capable of attaining close to 100% success rate in identifying matched contours.
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