26 February 2010 Genetic algorithm and evolvable hardware for adaptive filtration and analysis using texture, color, and boundary
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Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75463K (2010) https://doi.org/10.1117/12.856322
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore
Abstract
Image de-noising is usually required to be performed before further processing like segmentation, object recognition and texture analysis. This paper gives a novel method of combining the filtration process and the post-processing techniques. For this purpose , evolvable hardware is combined with Genetic Algorithm to offer potential cost efficiency together with the flexibility of an adaptive system, producing a high-speed non-linear adaptive median filter . The spatial domain filtering techniques discussed are various forms of median filtering from which the 'FITTEST' algorithm is chosen depending on user requirements . Adaptive median filter removes the impulse & salt and pepper noise efficiently while retaining the edges and other detailed features. Further , after filtration , an object in the image is represented on a scale of categories and recognition algorithms are used to find the most detailed category according to information extracted from the image. The categorization is based on the color and texture content of the image. Border detection is also done by classifying the pixels as homogeneous and heterogeneous by comparison with the neighboring pixels . These techniques can be effectively implemented to process aerial photographs and to detect oil spills in the sea and properties of the ocean useful for fishery and navigation.
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Vandana Venkatraman, Vandana Venkatraman, Soumya Raja, Soumya Raja, } "Genetic algorithm and evolvable hardware for adaptive filtration and analysis using texture, color, and boundary", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75463K (26 February 2010); doi: 10.1117/12.856322; https://doi.org/10.1117/12.856322
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