Image Classification Using Feature Subset Selection
نویسندگان
چکیده
Classification technology is essential for fast retrieval in large database. This paper proposes a combining GA and SVM model to content-based image retrieval. The proposed method is also used to classification similar images from database. Joint HSV histogram and average entropy computed from gray-level co-occurrence matrices in the localized image region is employed as input vectors. Genetic algorithm is employed to select feature subsets eliminated irrelevant factors as used inputs and to determine the optimal parameters of Support Vector Machine. Experimental results show that the proposed model outperforms existing method. Key-Words: SVM, Genetic Algorithm, CBIR, Feature Selection, Image
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