Abstract:
Authors have proposed novel multi-dimensional multi-directional mask maximum edge patterns for the bio-medical image
retrieval. Standard local binary patterns encode relationship of neighbor pixels with center pixel. Local mesh patterns encode
the relationship between adjacent pixels surrounding the center pixel. Proposed approach encodes relationship of neighbour
pixels in adjacent planes of a multi-dimensional image, in three stages. In the first stage, five sub images are formed by
traversing in five different directions on three planes of a multi-dimensional image. In the second stage, directional masks are
applied on each sub image to find directional edges. In stage three, maximum edge patterns are found based on the directions
of the directional edges. To examine performance analysis of the proposed algorithm, we tested proposed algorithm on
three benchmark databases, which gives retrieval accuracy 56.93% for top 5 images, 93.36 and 62.49% for top 10 images
on MESSIDOR (Retinal images), VIA/I-ELCAP (CT images) and OASIS-MRI databases respectively in terms of average
retrieval precision. The comparison reflects, there is considerable improvement in the performance.
