On improved deformable template matching for polygonal objects

In this paper, an improvement of deformable template matching algorithm for polygonal objects in grayscale images using two-dimensional deformable templates along orthogonal curves is presented. In the process of pre-computing extensions of the deformable template along orthogonal curves, the novel...

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Autores principales: Luo, Jianshu, Tang, Zeying, Lu, Hanqing
Formato: Articulo
Lenguaje:Inglés
Publicado: 2004
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Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9475
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr04-3.pdf
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Sumario:In this paper, an improvement of deformable template matching algorithm for polygonal objects in grayscale images using two-dimensional deformable templates along orthogonal curves is presented. In the process of pre-computing extensions of the deformable template along orthogonal curves, the novel matching approach incorporates adapting knowledge-specific template discretization techniques appropriate for different polygonal objects and minimizing the improved internal and external energy terms containing inter-shape information of polygonal objects. In our application, this energy optimization problem of the deformable template is efficiently solved by a genetic algorithm (GA). Our algorithm has been successfully applied on synthetic images and real images. The experiment results show that the new approach provides more robust and accurate matching method.