Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33104
Local Mesh Co-Occurrence Pattern for Content Based Image Retrieval
Authors: C. Yesubai Rubavathi, R. Ravi
Abstract:
This paper presents the local mesh co-occurrence patterns (LMCoP) using HSV color space for image retrieval system. HSV color space is used in this method to utilize color, intensity and brightness of images. Local mesh patterns are applied to define the local information of image and gray level co-occurrence is used to obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence pattern extracts the local directional information from local mesh pattern and converts it into a well-mannered feature vector using gray level co-occurrence matrix. The proposed method is tested on three different databases called MIT VisTex, Corel, and STex. Also, this algorithm is compared with existing methods, and results in terms of precision and recall are shown in this paper.Keywords: Content-based image retrieval system, HSV color space, gray level co-occurrence matrix, local mesh pattern.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1108124
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2223References:
[1] Christoph Palm, “Color texture classification by integrative Cooccurrence matrices,” Pattern Recognition, vol.37 pp. 965-976(2004)
[2] Fernando Roberti de Siqueira, William Robson Schwartz, and Helio Pedrini, “Multi-Scale Gray Level Co-Occurrence Matrices for Texture Description,” Neurocomputing, vol.120 pp. 336-345,2013
[3] Chuen-Horng Lin, Rong-Tai Chen, and Yung-Kuan Chan, “A smart content-based image retrieval system based on color and texture feature”, Image and Vision Computing, 2009, 27, 658-665.
[4] A. Vadivel, Shamik Sural, and A.K. Majumdar, “An Integrated Color and Intensity Co-occurrence Matrix”, Pattern Recognition Letters, vol.28, pp.974-983, 2007.
[5] Santosh Kumar Vipparthi, and Shyam Krishna Nagar, “Multi-joint histogram based modeling for image indexing and retrieval”, Computers and Electrical Engineering, vol.8 pp. 163-173, 2014.
[6] Xiaoyang Tan and Bill Triggs, “Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions”, In: Analysis and Modeling of faces and gestures, 168-182, 2007.
[7] Subrahmanyam Murala, Q.M. Jonathan Wu, R. Balasubramanian ; R.P. Maheshwari, “Joint histogram between color and local extrema patterns for object tracking”, Proc. SPIE 8663Video Surveillance and Transportation Imaging Applications, 2013.
[8] Baochang Zhang, Yongsheng Gao, Sanqiang Zhao, Jianzhuang Liu, Local derivative pattern versus local binary pattern: Face recognition with higher-order local pattern descriptor, IEEE Transactions on image processing, vol.19 pp.533-544, 2010.
[9] Subrahmanyam Murala, Q.M. Jonathan Wu, Local ternary cooccurrence patterns: A new feature descriptor for MRI and CT image retrieval, Neurocomputing, vol.119 pp.399-412,2013.
[10] Subrahmanyam Murala, R. P. Maheshwari, R. Balasubramanian , Local maximum edge binary patterns: A new descriptor for image retrieval and object tracking, Signal Processing, vol.92 pp.1467-1479,2012.
[11] K.P.Jasmine and P.Rajesh Kumar, Integration of HSV Color Histogram and LMEBP Joint Histogram for Multimedia Image Retrieval, Advances in Intelligent Systems and Computing, vol.243 pp. 753-762, 2014.
[12] Subrahmanyam Murala, R.P. Maheshwari, R. Balasubramanian , Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval, IEEE Transactions on Image Processing, vol. 21 pp. 2874- 2886, 2012.
[13] Cheng-Hao Yao, Shu-Yuan Chen, “Retrieval of translated, rotated and scaled color textures”, Pattern Recongition, vol.36 pp.913-929, 2003.
[14] Marko Heikkil¨, Matti Pietik¨ainen, Cordelia Schmid, Description of Interest Regions with Local Binary Patterns, in Computer Vision, Graphics and Image Processing, pp.58-69, 2006.
[15] Subrahmanyam Murala , Q.M. Jonathan Wu; R. Balasubramanian; R.P. Maheshwari, “Joint histogram between color and local extrema patterns for object tracking”, Proc. SPIE Video Surveillance and Transportation Imaging Applications, pp.86630T, 2013.
[16] Subramaniam Murala, Q. M. Jonathan Wu, “Local Mesh Patterns Versus Local Binary Patterns: Biomedical image indexing and retrieval” IEEE J. Bio. Health. Trans, vol.18 pp.2014, 929-938.