Abstract
This paper presents an efficient approach with the reduced length of feature vector for biomedical image retrieval by using global and local features of an image. In order to extract the local features, a new algorithm, local directional edge binary pattern (LDEBP) has been designed. It gathers information from all the possible directions, i.e., 00, 450, 900 and 1350 for every pixel in the image. The directional information is calculated based on the sign code magnitudes of local differences from the center pixel to its directional pixels. For every pixel, four edges will be calculated by using all the directional information. Lower order Zernike moments are used for extracting the global and shape features of an image. The combination of shape and texture descriptors for biomedical image retrieval showed significant results compared to the state of the art algorithms like LDEP, ZM and LBDP on benchmark database like Emphysema-CT and OASIS-MRI.
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