Affine invariant matching of broken boundaries based on simple genetic algorithm and contour reconstruction

Authors:
P. W. M. Tsang;W. C. Situ
Affiliations:
Department of Electronic Engineering, City University of Hong Kong, Hong Kong;Department of Electronic Engineering, City University of Hong Kong, Hong Kong
Venue:
Pattern Recognition Letters
Year:
2010

Citing 12
Cited 1

Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm

IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic contour matching

Pattern Recognition Letters - Special issue on genetic algorithms
A genetic algorithm for affine invariant recognition of object shapes from broken boundaries

Pattern Recognition Letters
Partial shape matching using genetic algorithms

Pattern Recognition Letters
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Evaluation of genetic operators and solution representations for shape recognition by genetic algorithms

Pattern Recognition Letters
Genetic algorithm for affine point pattern matching

Pattern Recognition Letters
Efficient contour-based shape representation and matching

MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Coarse-to-Fine Multiscale Affine Invariant Shape Matching and Classification

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Applying Genetic Algorithms on Pattern Recognition: An Analysis and Survey

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
2D Affine-Invariant Contour Matching Using B-Spline Model

IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine invariant object shape matching using genetic algorithm with multi-parent orthogonal recombination and migrant principle

Applied Soft Computing

Fast affine invariant shape matching from 3d images based on the distance association map and the genetic algorithm

ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV

Quantified Score

Hi-index	0.10

Visualization

Abstract

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.