Title :
Object Identification Based on Deformable Templates and Genetic Algorithms
Author :
Moni, M.A. ; Ali, A. B M Shawkat
Author_Institution :
Dept. of Comput. Sci. & Eng., Jatiya Kabi Kazi Nazrul Islam Univ., Bangladesh
Abstract :
In this paper, an algorithm is described which detects and localizes shapes in grayscale images. Deformable templates are often employed to model the geometry of the object to be found in an image. There are several methods to find the optimal placement and deformation of the template onto the image. A genetic algorithm is designed which takes the object template and processed grayscale image and locates the object in the image, invariant to rotation, translation and scale. The limitations of processing the image before running the genetic algorithm (GA) are discussed.
Keywords :
edge detection; genetic algorithms; object recognition; Canny edge detection; deformable templates; evolutionary algorithm; genetic algorithms; grayscale images; object identification; object recognition system; Algorithm design and analysis; Deformable models; Evolutionary computation; Genetic algorithms; Genetic engineering; Genetic mutations; Geometry; Gray-scale; Object recognition; Solid modeling; Deformable templates; Evolutionary algorithm; Genetic algorithm; Object identification;
Conference_Titel :
Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3705-4
DOI :
10.1109/BIFE.2009.198