A Study on Feature Points Matching for Object Recognition Using Genetic Algorithm 


Vol. 6,  No. 4, pp. 1120-1128, Apr.  1999
10.3745/KIPSTE.1999.6.4.1120


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  Abstract

The model-based object recognition is defined as a graph matching process between model images and an input image. In this paper, a graph matching problem is modeled as an optimization problem and a genetic algorithm is proposed to solve the problem. For this work, fitness function, data structure, and genetic operators are developed. The simulation results are shown that the proposed genetic algorithm can match feature points between model image and input image for recognition of partially occluded two-dimensional objects. The performance of the proposed technique is compared with that of a neural network technique.

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[IEEE Style]

L. J. Ho and P. S. Ho, "A Study on Feature Points Matching for Object Recognition Using Genetic Algorithm," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 6, no. 4, pp. 1120-1128, 1999. DOI: 10.3745/KIPSTE.1999.6.4.1120.

[ACM Style]

Lee Jin Ho and Park Sang Ho. 1999. A Study on Feature Points Matching for Object Recognition Using Genetic Algorithm. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 6, 4, (1999), 1120-1128. DOI: 10.3745/KIPSTE.1999.6.4.1120.

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