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AUTOMATIC IMAGE CATEGORIZATION AND ANNOTATION USING K-NN FOR COREL DATASETKeywords: Automatic image annotation , Color features , Texture features , K- Nearest Neighbor , Multiple Instance Learning. Abstract: The search of an image in image database using keywords is made powerful due to automatic image annotation. In this paper, an automatic image annotation using K- Nearest Neighbor (K-NN) is presented. The categorization based approach is presented for annotation. Images are first segmented using k-means clustering and then processed to form feature vector. Local features are extracted from the regions of the image. The feature vectors are experimented using K-NN. Our system is validated using ten categories from the COREL images. It is observed that in multiple instance learning using K-NN with color and texture features outperforms for all type of feature vectors.
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