Description

In this paper, we propose GLCM (Gray Level Co-occurrence Matrix) and Tamura based feature extraction for image retrieval. The GLCM feature extraction methods gives the feature values of image contrast feature, autocorrelation feature, entropy feature, dissimilarity feature, homogeneity feature, (etc.). The Tamura feature extraction method gives the values of coarseness, contrast, directionality, line-likeness, regularity and roughness. The combination of both GLCM and Tamura feature extraction will make efficient in the image retrieval. This approach is better than existing methods because here the system uses both the advantages of GLCM and Tamura. In our system we first extract the feature values for all the database collected images and store the values separately. If a test image given as the input to the system the feature values for the given image have to extract and finally according to the feature value, the relevant images are retrieved from the database.