DocumentCode :
78921
Title :
Local Mesh Patterns Versus Local Binary Patterns: 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
Volume :
18
Issue :
3
fYear :
2014
fDate :
May-14
Firstpage :
929
Lastpage :
938
Abstract :
In this paper, a new image indexing and retrieval algorithm using local mesh patterns are proposed for biomedical image retrieval application. The standard local binary pattern encodes the relationship between the referenced pixel and its surrounding neighbors, whereas the proposed method encodes the relationship among the surrounding neighbors for a given referenced pixel in an image. The possible relationships among the surrounding neighbors are depending on the number of neighbors, P. In addition, the effectiveness of our algorithm is confirmed by combining it with the Gabor transform. To prove the effectiveness of our algorithm, three experiments have been carried out on three different biomedical image databases. Out of which two are meant for computer tomography (CT) and one for magnetic resonance (MR) image retrieval. It is further mentioned that the database considered for three experiments are OASIS-MRI database, NEMA-CT database, and VIA/I-ELCAP database which includes region of interest CT images. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP, LBP with Gabor transform, and other spatial and transform domain methods.
Keywords :
biomedical MRI; computerised tomography; image retrieval; medical image processing; CT image retrieval; Gabor transform; MR image retrieval; NEMA-CT database; OASIS-MRI database; VIA/I-ELCAP database; biomedical image databases; biomedical image indexing; biomedical image retrieval; computer tomography image retrieval; local binary patterns; local mesh patterns; magnetic resonance image retrieval; referenced pixel; spatial domain methods; surrounding neighbors; transform domain methods; Biomedical imaging; Feature extraction; Image retrieval; Informatics; Wavelet transforms; Biomedical image retrieval (CBIR); Gabor transform (GT); local binary pattern (LBP); local mesh patterns (LMeP); texture;
fLanguage :
English
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
Publisher :
ieee
ISSN :
2168-2194
Type :
jour
DOI :
10.1109/JBHI.2013.2288522
Filename :
6654267
Link To Document :
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