Title :
Peak Valley Edge Patterns: A New Descriptor for Biomedical Image Indexing and Retrieval
Author :
Murala, Subrahmanyam ; Wu, Q. M. Jonathan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
Abstract :
A new algorithm meant for biomedical image retrieval application is presented in this paper. The local region of image is represented by peak valley edge patterns (PVEP), which are calculated by the first-order derivatives in 0°, 45°, 90° and 135° directions. The PVEP differs from the existing local binary pattern (LBP) in a manner that it extracts the directional edge information based on first-order derivative in an image. Further, the effectiveness of our algorithm is confirmed by combining it with Gabor transform. The performance of the proposed method is tested on VIA/I-ELCAP database which includes region of interest computer tomography (ROI-CT) images. Performance analysis shows that the proposed method improves retrieval results from 79.21% to 86.13% and 51.91% to 55.06% as compared to LBP in terms of average precision when number of top matches considered is 10 and 100 respectively.
Keywords :
Gabor filters; computerised tomography; image representation; image retrieval; indexing; medical image processing; transforms; Gabor transform; LBP; PVEP; ROI-CT image; VIA/I-ELCAP database; biomedical image indexing; biomedical image retrieval; directional edge information extraction; first-order derivatives; image local region representation; local binary pattern; peak valley edge patterns; performance analysis; region of interest computer tomography image; Biomedical imaging; Computed tomography; Feature extraction; Image edge detection; Image retrieval; Transforms; Biomedical; Features; Image Retrieval; Local Binary Patterns (LBP);
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
Conference_Location :
Portland, OR
DOI :
10.1109/CVPRW.2013.73