Medical Image Retrieval Based on Gray Cluster Co-occurrence Matrix and Edge Strength Levels

Retrieving images depend of specific features In Content Based Image Retrieval (CBIR). A common approach is to divide retrieval process into two stages; the first one is based on high-level features followed by the second that is based on low-level features. We focus primarily on medical images, and follow the above approach but make the following two basic contributions: a) introduce the gray cluster co-occurrence matrix as texture feature extraction and use it as high-level features, and b) introduce edge strength levels as shape feature extraction and use it as low-level features. Our proposed system suggests the precision rate was 94.90% and recall rate was 89.72%. The distance variance achieved lowest rate (0.0022) in images retrieval compared to each of partial systems individually and related works. Our method has better performance in retrieving the results than other related works and each of partial system individually.