ENHANCING IMAGE RETRIEVAL EFFICIENCY WITH SPATIAL DEPENDENCE MATRIX AND TRANSLATION INVARIANT DISCRETE WAVELET TRANSFORM

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Salandri Abhishesk Yadav
Hima Bindu Kunchanapalli
A. Poornima

Abstract

The present study describes the implementation of a highly effective content-based image retrieval (CBIR) system. This system utilizes an integrated approach for feature extraction, incorporating the use of a spatial dependence matrix (SDM) to extract texture features from the provided images. Additionally, a translation invariant discrete wavelet transform (TIDWT) is employed for low-level feature extraction. Moreover, the effectiveness of the proposed hybrid Content-Based Image Retrieval (CBIR) system was evaluated using the Tanimoto distance. The results of a comprehensive experimental investigation reveal that the suggested hybrid Content-Based Image Retrieval (CBIR) system exhibits a significant enhancement in efficiency when compared to standard CBIR systems.

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How to Cite
Yadav, S. A. ., Kunchanapalli, H. B., & Poornima, A. . (2021). ENHANCING IMAGE RETRIEVAL EFFICIENCY WITH SPATIAL DEPENDENCE MATRIX AND TRANSLATION INVARIANT DISCRETE WAVELET TRANSFORM. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(8), 3312–3317. https://doi.org/10.61841/turcomat.v12i8.14345
Section
Research Articles

References

D. Feng, W. C Siu, and H.J. Zhang, “Fundamentals of Content Based Image Retrieval, in Multimedia Information

Retrieval and Management Technological Fundamentals and Applications”, New York: Springer, 2003.

A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, “Content-based image retrieval at the end of the

early years,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, pp. 1349–1380, Dec-2000.

Khan, S.M.H., Hussain, A. ; Alshaikhi, I.F.T., “Comparative Study on Content Based Image (CBIR),” International

Conference in Advanced Computer Science Applications and Technologies (ACSAT), 2012.

Wan Siti, H. Munirah, W. Ahmad, M. Faizal and A. Fauzi, “Comparison of Different Feature Extraction Techniques

in Content Based Image Retrieval For CT Brain Images,” 10Th IEEE workshop on Multimedia Signal Processing,

pp. 503-508, 2008.

B. S. Manjunath, J. R. Ohm, V. V. Vasudevan, A.Yamada, “Colour and Texture Descriptors,” IEEE Transactions on

Circuits and Systems for Video Technology, 1998.

P. S. Hiremath, S. Shivashankar, J. Pujari, “Wavelet Based Features for Color Texture classification with Application

to CBIR,” International Journal of Computer Science and Network Security, Vol. 6, No.9A, September 2006.

Tian Yumin, Mei Lixia, “Image Retrieval Based on Multiple Features Using Wavelet,” 5th IEEE International

Conference on Computational Intelligence and Multimedia Applications (ICCIMA’03), 2003.

M. R. Zare, R. N. Ainon, W. C. Seng, “Content-based Image Retrieval for Blood Cells,” Third Asia International

Conference on Modeling & Simulation, 2009.

Prasad, B.G., Krishna, A.N., “Statistical Texture Feature Based Retrieval and Performance Evaluation of CT Brain

Images” 3rd International Conference on Electronics Computer Technology (ICECT), Vol. 2, April 2011.

Swati Agarwal, A.K. Verma, Preethvanti Singh, “Content Based Image Retrieval using Discrete Wavelet Transform

and Edge Histogram Descriptor” International conference on Information Systems and Computer Networks, 2013.

M. A. Ansari and M. Dixit, “An enhanced CBIR using HSV quantization, discrete wavelet transform and edge

histogram descriptor”, International Conference on Computing, Communication and Automation, IEEE, Greater

Noida, India, May 2017.

D. R. Dhotre, G. R. Bamnote and P. H. Shekokar, “Multilevel Haar wavelet transform and histogram based relevant

image retrieval system”, International Conference on Computing Methodologies and Communication, IEEE, Erode,

India, July 2017.

A. Nazir, R. Ashraf, T. Hamdani and N. Ali, “Content based image retrieval system by using HSV color histogram,

discrete wavelet transform and edge histogram descriptor”, International Conference on Computing, Mathematics and

Engineering Technologies, IEEE, Sukkur, Pakistan, Mar. 2018.

F. Nausheen, R. Kamble and M. Kokare, “Image Retrieval based on Wavelet and Optimized Local Gaussian

Difference Extrema Pattern”, IEEE 13th International Conference on Industrial and Information Systems, Rupnagar,

India, Dec. 2018.