Content-based retrieval of biomedical images using orthogonal Fourier-Mellin moments

Biomedical imaging field is growing enormously from last decade. The medical images have been used and stored continuously for diagnosis as well as research purposes. For real-time retrieval of medical images from such storage repositories, there is a grave need of an effective and efficient biomedical image indexing and retrieval approach. In this quest, this paper presents a new approach for the retrieval of CT and MR images using orthogonal Fourier-Mellin moments (OFMMs). OFMMs have excellent information representation capability that enables them to pack the entire image information in very less number of coefficients. This property makes the proposed approach not only effective but also computationally very efficient and most favourable among all the existing approaches. The proposed approach has been tested and compared with numerous existing, state-of-the-art as well as recently published biomedical indexing and retrieval approaches on two standard databases namely, NEMA CT and NEMA MRI. Additional experiments have been conducted to analyse the noise robustness ability of the proposed and all the compared approaches. The reported results show superior retrieval performance of the proposed approach and a significant increase in the retrieval rate over all the existing approaches on noisy images on both the test databases.