Designing a Shape-Based Image Retrieval System by Grey Relational Analysis and GM(1,N) Model

Abstract

With the explosive growth of multimedia applications, the quality and ability to retrieve images in an efficient way is a challenge to researchers. A new shape-based image retrieval model is presented to improve the recall rate of image retrieval system. The retrieval procedures consist of two major steps: the feature representation of object's shape and the image retrieval method. The shape signatures are extracted along the object boundary to form a data sequence for grey model. After deriving the feature sequences, both grey relational analysis and GM(1,N) model are integrated to construct the proposed image retrieval model. A fish data set is selected to test the reconstructed error rates when different comparative images are chosen for the GM(1,N) model. Experimental results from the fish shape library verify the effectiveness of the proposed model.