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In this paper, the advantages of ensemble methods are applied to image categorization. A novel method is introduced for image categorization by combining various visual vocabularies with different sizes in the popular vocabulary approach. The vocabulary approach describes an image as a bag of discrete visual codewords, where the frequency distributions of these words are used for image categorization...
This paper presents a new bag-of-words based algorithm for object recognition. Our algorithm also includes five steps: feature detection and representation, codebook generation, learning and recognition. All features are extracted as dense grids of images instead of interest point for computationally efficiency and effectiveness. While features are described by histograms of oriented gradients (HOG)...
A hierarchical classification matching scheme for fractal image compression is proposed in this paper. This scheme reduces the encoding time dramatically by partitioning the domain pools hierarchically. Experimental results on standard gray scale image show that the hierarchical classification matching scheme yields much better performance over other classification matching scheme. Compared with Fisherpsilas...
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