Biomedical Image Indexing and Retrieval Descriptors: A Comparative Study

Abstract This paper focuses on the comparison of two new proposed pattern descriptors i.e., local mesh ternary pattern (LMeTerP) and directional local ternary quantized extrema pattern (DLTerQEP) for biomedical image indexing and retrieval. The standard local binary patterns (LBP) and local ternary patterns (LTP) encode the gray scale relationship between the center pixel and its surrounding neighbors in two dimensional (2D) local region of an image whereas the former descriptor encodes the gray scale relationship among the neighbors for a given center pixel with three selected directions of mess patterns which is generated from 2D image and later descriptor encodes the spatial relation between any pair of neighbors in a local region along the given directions (i.e., 0, 45, 90 and 135) for a given center pixel in an image. The novelty of the proposed descriptors is that they use ternary patterns from images to encode more spatial structure information which lead to better retrieval. The experimental results demonstrate the superiority of the new techniques in terms of average retrieval precision (ARP) and average retrieval rate (ARR) over state-of-the-art feature extraction techniques (like LBP, LTP, LQEP, LMeP etc.) on three different types of benchmark biomedical databases.

[1]  P.K. Biswas,et al.  Rotation-Invariant Texture Image Retrieval Using Rotated Complex Wavelet Filters , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[3]  Minh N. Do,et al.  Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance , 2002, IEEE Trans. Image Process..

[4]  Richard G. Baraniuk,et al.  Multiscale image segmentation using wavelet-domain hidden Markov models , 2001, IEEE Trans. Image Process..

[5]  Chi-Ren Shyu,et al.  Knowledge-Driven Multidimensional Indexing Structure for Biomedical Media Database Retrieval , 2007, IEEE Transactions on Information Technology in Biomedicine.

[6]  Xiaoyang Tan,et al.  Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions , 2007, IEEE Transactions on Image Processing.

[7]  Prabir Kumar Biswas,et al.  Texture image retrieval using rotated wavelet filters , 2007, Pattern Recognit. Lett..

[8]  Subrahmanyam Murala,et al.  Local ternary co-occurrence patterns: A new feature descriptor for MRI and CT image retrieval , 2013, Neurocomputing.

[9]  Agma J. M. Traina,et al.  Retrieval by content of medical images using texture for tissue identification , 2003, 16th IEEE Symposium Computer-Based Medical Systems, 2003. Proceedings..

[10]  Zhenhua Guo,et al.  Rotation invariant texture classification using LBP variance (LBPV) with global matching , 2010, Pattern Recognit..

[11]  D. Venkata Rao,et al.  Local quantized extrema patterns for content-based natural and texture image retrieval , 2015, Human-centric Computing and Information Sciences.

[12]  Bertrand Zavidovique,et al.  Content based image retrieval using motif cooccurrence matrix , 2004, Image Vis. Comput..

[13]  Subrahmanyam Murala,et al.  Directional local extrema patterns: a new descriptor for content based image retrieval , 2012, International Journal of Multimedia Information Retrieval.

[14]  Bill Triggs,et al.  Visual Recognition Using Local Quantized Patterns , 2012, ECCV.

[15]  Loris Nanni,et al.  Local binary patterns variants as texture descriptors for medical image analysis , 2010, Artif. Intell. Medicine.

[16]  Prabir Kumar Biswas,et al.  Texture image retrieval using new rotated complex wavelet filters , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[17]  R. Balasubramanian,et al.  Local maximum edge binary patterns: A new descriptor for image retrieval and object tracking , 2012, Signal Process..

[18]  Subrahmanyam Murala,et al.  Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval , 2012, IEEE Transactions on Image Processing.

[19]  Marko Heikkilä,et al.  Description of interest regions with local binary patterns , 2009, Pattern Recognit..

[20]  John G. Csernansky,et al.  Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults , 2007, Journal of Cognitive Neuroscience.

[21]  Matti Pietikäinen,et al.  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2009, TPAMI-2008-09-0620 1 WLD: A Robust Local Image Descriptor , 2022 .

[22]  Subrahmanyam Murala,et al.  Directional Binary Wavelet Patterns for Biomedical Image Indexing and Retrieval , 2012, Journal of Medical Systems.

[23]  Loris Nanni,et al.  Local binary patterns for a hybrid fingerprint matcher , 2008, Pattern Recognit..

[24]  Zhiqiang Zhou,et al.  Binary Gabor pattern: An efficient and robust descriptor for texture classification , 2012, 2012 19th IEEE International Conference on Image Processing.

[25]  Baochang Zhang,et al.  Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor , 2010, IEEE Transactions on Image Processing.

[26]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[28]  Subrahmanyam Murala,et al.  MRI and CT image indexing and retrieval using local mesh peak valley edge patterns , 2014, Signal Process. Image Commun..

[29]  Subrahmanyam Murala,et al.  Local Mesh Patterns Versus Local Binary Patterns: Biomedical Image Indexing and Retrieval , 2014, IEEE Journal of Biomedical and Health Informatics.