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6 July 1998 GALE: a combined genetic algorithm-linear technique approach to edge detection
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Image enhancement applications are highly dependent on the efficiency of edge detection techniques. Most of these techniques have a time complexity of O(n2) where the picture has size n X n. The use of more advanced algorithms can substantially reduce this requirement, improving the computational performance of the application. This paper presents a new method, named GALE, which combines the random search mechanisms of Genetic Algorithms with linear time methods. The resulting edge detection process approaches linear time complexity as demonstrated in the experiments also reported here. The Genetic Algorithm is constructed by utilizing a fitness measurement which is proportional to a directional gradient to select picture windows and establishes candidate pairs of points which bracket an edge. Such areas are then investigated by using near-neighbor linear techniques and the Sobel number for edge identification and detection. The linear technique procedures are built in such a way that the use of other fitness functions, such as the Sombrero operator, instead of the Sobel number are easily implemented and activated. The paper begins by discussing related work in this area, following by the description of the basic concepts of Genetic Algorithms required for this solution. A detailed view of the linear search algorithm is then presented, followed by a report on some experiments conducted in a controlled environment. Theoretical results are used to support the evidence of the time complexity and correctness of this new method. In addition, the experimental results show the improved performance of this method.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Timothy P. Donovan and Nelson Luiz Passos "GALE: a combined genetic algorithm-linear technique approach to edge detection", Proc. SPIE 3387, Visual Information Processing VII, (6 July 1998);


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