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Optical Disc Detection on Retina Image Using VLSI Genetic Optimization Technique
Abstract
Hough transform is used for detecting circles in an image. To reduce the huge computations in Hough transform, a resource efficient architecture is essential. Resource efficient and reduction in processing time are achieved with data parallelism. We present a circle detection method based on genetic algorithms. Our genetic algorithm uses the encoding of three edge points as the chromosome of candidate circles (x, y, and r) in the edge image of the scene. Fitness function evaluates if these candidate circles are really present in the edge image. Our encoding scheme reduces the search space by avoiding trying unfeasible individuals, this result in a fast circle detector. The implementation of GA-based Hough transform on an FPGA. This architecture is implemented using alter a device at operating frequency of 200MHz. It compute the Hough transform of 512x512 test images with 180 orientation in 2.05 to 3.15ms with minimum number of FPGA resources.
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References
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