Combined Weighted Feature Extraction and Dimension Reduction (CWFE-DR) Technique for CBIR
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Abstract
Content-Based Image Retrieval (CBIR) obtains information from images by utilizing the features lines, textures, colors and spatial data. The performance of the CBIR system can be speed up by reducing the size of the training images. This paper proposes a Combined Weighted Feature Extraction and Dimension Reduction (CWFE-DR) technique for CBIR. In this technique, the images which are onlysimilar to the query image are fetched. The performance is further enhanced by generating a combined feature vector based on color, shape and texture features. By applying multiclass Support Vector Machine (SVM), the appropriate weights of the individual features are determined adaptively, depending on the type of query image.
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