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22 August 1995 Object recognition using simulated annealing and Fourier descriptors
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In this paper a method for object recognition is proposed. This method combines some local characteristics of the image, such as the location and intensity of the edges with some priory information about the possible shape of the object in order to recognize objects in a noisy or faded image. Finding objects in an aerial photograph could be considered as a good example of such images. The method implements the above idea by defining a function which includes a number of measures of some properties of the image as its terms. Each of these measures is defined so as to take its minimum value when the corresponding property is best met. This function is called the objective function. In our approach the object recognition problem is defined as a minimization of an objective function with terms which include the sharpness of the edges of the object, the smoothness of the object and its level of similarity with the predefined models. Simulated annealing has been employed for the minimization of this objective function. Fourier descriptors have been used to represent the shape of the objects which, with some modifications, can result in a rotation, scale, and translation invariant recognition system. The results obtained by applying the method to aerial photographs indicate its good ability to locate and recognize complex regions.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Majid Raissi, F. Hariri, Ahmad R. Mirzai, and G. H. Roeintan "Object recognition using simulated annealing and Fourier descriptors", Proc. SPIE 2564, Applications of Digital Image Processing XVIII, (22 August 1995);

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