Title :
Fitness function evaluation for the detection of multiple ellipses using a genetic algorithm
Author :
Cruz-Díaz, César ; De la Fraga, Luis Gerardo ; Schütze, Oliver
Author_Institution :
Comput. Sci. Dept., CINVESTAV-IPN, Mexico City, Mexico
Abstract :
In this paper, we use a genetic algorithm (GA) for the detection and fitting of multiple ellipses which are implicitly given by a data set which contains noisy data. The overall aim is to quickly detect the entire set of ellipses, without additional information about the sizes, and shapes of the ellipses, and the amount of noise in the data set, but knowing the number of ellipses and providing a threshold value. In this work, we develop and investigate-based on a standard GA-three different fitness functions which have different advantages and disadvantages. From numerical results we verify that we are yet able to reliably and efficiently compute the set of ellipses in certain situations.
Keywords :
genetic algorithms; ellipse fitting; ellipses detection; fitness function evaluation; genetic algorithm; Approximation methods; Genetic algorithms; Mathematical model; Noise; Robustness; Stochastic processes; Transforms; Ellipse fitting; Hausdorff distance; fitness function; genetic algorithms; robust fitting;
Conference_Titel :
Electrical Engineering Computing Science and Automatic Control (CCE), 2011 8th International Conference on
Conference_Location :
Merida City
Print_ISBN :
978-1-4577-1011-7
DOI :
10.1109/ICEEE.2011.6106652