Object based similarity measure for breast medical image retrieval from data warehouse

Authors:
Hyun I. Kim;Donghoon Kang;Byung K. Jung;Chang Oan Sung
Affiliations:
South Dakota State University, Brookings, SD;South Dakota State University, Brookings, SD;South Dakota State University, Brookings, SD;Indiana University Southeast, New Albany, IN
Venue:
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Year:
2012

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Abstract

In this paper, we propose a new binary pixel matching method to measure the similarity of two objects based on the overlapped areas in a data warehouse. In the proposed approach, suspicious objects are extracted as binary images that consist of background and foreground, which are compared based on counting overlapped pixels. Before measuring the exact similarity between two objects, we calculate a difference in the shape index, perform rotation normalization, then, estimate accurate similarity, if the difference in the shape index is less than 50%. The results demonstrate that the proposed approach can significantly improve both the accuracy of similarity measurement and the performance of computational speed, when compared with traditional content based image retrieval method approaches that measure the similarity based on contours.