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Image Search by comparing Gabor filter with SVM and SIFT

Suman S. Bhujbal*, Shubhangi R. Patil**

* PG Scholar, Department of Computer Engineering, A.C. Patil College of Engineering, Kharghar, Maharashtra, India.

** Assistant Professor, Department of Computer Engineering, A.C. Patil College of Engineering, Kharghar, Maharashtra, India.

Periodicity:June - August'2018
DOI : https://doi.org/10.26634/jit.7.3.14403

Abstract

Social image search is becoming popular day by day, lots of research is going on in Image search systems. Some image searching technique matches only textual or visual features of image for searching. Many Image searching methods combine visual features and textual feature of image for better performance. Hypergraph Learning Technique finds more relevant image. Some image search algorithms make use of SIFT features. This paper shows that, the results of Gabor with SVM have better results than SIFT.

Keywords

Component, Scale Invariant Feature Transform (SIFT), Gabor, Visual, Textual, Support Vector Machine (SVM).

How to Cite this Article?

Bhujbal,S.S., and Patil,S.R.(2018). Image Search by Comparing Gabor Filter With SVM and SIFT. i-manager’s Journal on Information Technology, 7(3), 10-16. https://doi.org/10.26634/jit.7.3.14403

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