Gray scale morphological operations for image retrieval

Content Based Image Retrieval (CBIR) systems serve as a powerful tool, which allows a user to compare a query image to previously obtained database images. Feature extraction and similarity measurement are the main characteristics of CBIR. Features such as shapes and texture are extracted from the query and reference images and are compared by means of Euclidean distance. The morphological operation with spatially-variant structuring element is used for feature extraction. After the feature extraction process, the feature vectors are calculated by applying Block Truncation coding (BTC) over the feature extracted images. It improves the performance of image retrieval with reduced computational complexity for query execution. Then the distance between the feature vectors are computed using Euclidean distance measurement. The performance of the proposed system is evaluated by the precision rate and recall rate.