Trademark Image Retrieval Using 3-D Color Histogram Approach

Latika Pinjarkar*, Manisha Sharma**, Smita Selot***
* Associate Professor, Department of Information Technology, Shri Shankaracharya Technical campus, Bhilai (C.G.), India.
** Professor and Head, Department of Electronics and TeleCommunication, Bhilai Institute of Technology, Bhilai (C.G.), India.
*** Professor and Head, Department of Master of Computer Application, Shri Shankaracharya Technical Campus, Bhilai (C.G.), India.
Periodicity:September - November'2015
DOI : https://doi.org/10.26634/jpr.2.3.3759

Abstract

Products and services available in the market in the form of brands that make trade practices are very important. Nowadays in the market, brand name is becoming very important. Every organization must have it's unique trademark or logo for uniqueness. Therefore designing an efficient trademark retrieval system and its evaluation for distinctiveness is thus becoming a very tedious job nowadays. Trademark Image Registration is one of the important application area of Content Based Image Retrieval (CBIR). Trademark image registration, where a new candidate mark is compared with the existing marks to ensure that there is no risk of confusion, has long been recognized as a prime application area of CBIR [1]. In the proposed work, a CBIR system is designed for trademark image retrieval based on 3D color histogram (HSV values) technique. The color histogram has the advantages of rotation and translation invariance and it has the disadvantages of lack of spatial information. The experiments were conducted on a database of few trademark images. The performance of the system was evaluated using standard evaluation parameters precision and recall.

Keywords

CBIR, Trademark, Color Feature Extraction, Color Histogram

How to Cite this Article?

Pinjarkar, L., Sharma, M., and Selot, S. (2015). Trademark Image Retrieval Using 3-D Color Histogram Approach. i-manager’s Journal on Pattern Recognition, 2(3), 24-29. https://doi.org/10.26634/jpr.2.3.3759

References

[1]. Latika Pinjarkar, & Manisha Sharma, (2011). “Content Based Image Retrieval for Trademark Registration: A Survey”. International Journal of Advanced Research in Computer and Communication Engineering, Vol. 2, No.11, pp. 4424-4430.
[2]. Gonzales R. C. and Woods R. E. (2002). Digital image processing, Prentice-Hall, Inc., 2nd edition, New Jersey.
[3]. Greg, & Ramin Zabih, (1995). “Histogram Refinement for Content-Based Image Retrieval”, Computer Science Department, Cornell University, Ithaca, NY 14853.
[4]. Wynne Hsu, T. S. Chua, and H. K. Pung, (1995), “An integrated color-spatial approach to content-based image retrieval”, ACM Multimedia Conference, pp. 305- 313.
[5]. Rickman Rick and Stonham John, (1996). “Contentbased image retrieval using color tuple histograms”, SPIE Proceedings, Vol. 2670, pp. 2-7.
[6]. John Smith and Shih-Fu Chang, (1996). “Tools and techniques for color image retrieval”, SPIE Proceedings, Vol. 2670, pp.1630-1639.
[7]. Markus Stricker and Alexander Dimai, (1996). “Color indexing with weak spatial constraints”, SPIE Proceedings, Vol. 2670, pp. 29-40.
[8]. Fuhui Long, Hongjiang Zhang, and David Dagan Feng, (2003). Multimedia Information Retrieval and Management: Chapter-1 Fundamentals of Content- Based Image Retrieval, Springer Berlin, Heidelberg, pp. 1- 26.
[9]. Virginia Ogle and Michael Stonebraker, (1995), “Chabot: Retrieval from a relational database of images”, IEEE Computer, Vol. 28, No. 9, pp. 40-48.
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