Image Retrieval Using Combination of Texture and Shape Features

The purpose of this research paper is retrieval of images from the image database using Content Based Image retrieval (CBIR) technique. It uses a novel approach which is a combination of texture and shape features. The K-means clustering and Fuzzy C-means clustering are used for segmenting the images. Then, the 5 Haralick texture features and 7 shape features are extracted. The extracted features are combined together. In our experiment, Corel database of image containing 1000 having 10 categories each of which has 100 images is used. The results are compared with other existing methods and it is found that the proposed combined features are better in retrieval of images than the other methods. Euclidean distance and Hausdroff distance are used for similarity measurements in the proposed CBIR method.

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