ABSTRACT
This paper presents a system supporting tuning and evaluation of a Content-Based Image Retrieval (CBIR) engine for vector images, by a graphical interface providing query-by-sketch and query-by-example interaction with query results, and analysis of result quality. Vector images are first modelled as an inertial system and then they are associated with descriptors representing visual features invariant to affine transformation. To support requirements of different application domains, the engine offers a variety of moment sets as well as difierent metrics for similarity computation. The graphical interface offers tools that helps in the selection of criteria and parameters necessary to tune the system to a specific application domain.
- M. M. Babu, M. Kankanhalli, and W. F. Lee. Shape measures for content based image retrieval: a comparison. Information Processing and Management, 33(3):319--337, 1997. Google ScholarDigital Library
- Y. C. Chim, A. A. Kassim, and Y. Ibrahim. Character recognition using statistical moments. Image and Vision Computing, 17:299--307, 1997.Google ScholarCross Ref
- T. Di Mascio and L. Tarantino. Main features of a cbir prototype supporting cartoon production. In 10th International Human Computer Interaction (HCI2003), volume 1, pages 921--925, 2003.Google Scholar
- G. Gagaudakis and P. Rosin. Shape measures for image retrieval. In IEEE International Conference on Image Processing, pages 757--760. IEEE, 2001.Google ScholarCross Ref
- H. R. Hartson, T. S. Andre, and R. C. Williges. Criteria for evaluating usability evaluation methods. International Jurnal of Human Computer Interaction, 15(1):145--181, 2003.Google ScholarCross Ref
- M. K. Hu. Visual pattern recognition by moments invariants. IRE Transactions on Information Theory, 8:179--187, 1997.Google Scholar
- D. Kapur, Y. N. Lakshman, and T. Saxena. Computing invariants using elimination methods. In IEEE International Conference on Computer Vision. IEEE, November 1995. Google ScholarDigital Library
- Scalable Vector Graphics (SVG), W3 Consortium, http://www.w3.org/Graphics/SVG/Google Scholar
- 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 Trans. on Pattern Analysis and Machine Intelligence, 22(12):1349--1380, 2000. Google ScholarDigital Library
- O. D. Trier, A. K. Jain, and T. Taxt. Feature extraction methods for character recognition: a survey. Pattern Recognition, 29(4):641--662, 1996.Google ScholarCross Ref
- S. E. Umbaugh. Computer vision and image processing. Prentice Hall International, 1998. Google ScholarDigital Library
- V. Vennarini and G. Todesco. Tools for paperless animation. Tech. report, IST Project fact sheet, 2001. http://inf2.pira.co.uk/mmctprojects/paperless.htm.Google Scholar
- L. Yang and F. Albregtsen. Fast and exact computation of cartesian geometric moments using discrete green's theorem. Pattern Recognition, 29(7):1061--1073, 1996.Google ScholarCross Ref
- L. Yang and F. Algregtsen. Fast computation of invariant geometric moments: a new method giving correct results. In IEEE International Conference on Pattern Recognition, pages 201--204, 1994.Google Scholar
Index Terms
- Tuning a CBIR system for vector images: the interface support
Recommendations
A Similarity Retrieval of Trademark Images Considering Similarity for Local Objects Using Vector Images
ICSPS 2016: Proceedings of the 8th International Conference on Signal Processing SystemsIn similarity retrievals of trademark images, evaluation of similarity for essential objects which show products or services is required. In order to examine similarity of local objects in images, it is necessary to extract the objects; however, it is ...
A framework of CBIR system based on relevance feedback
IITA'09: Proceedings of the 3rd international conference on Intelligent information technology applicationContent-based image retrieval (CBIR) is an effective approach for obtaining desired image, however, due to the semantic gap between low-level visual features and high-level concept of image, CBIR system of state-of-the-art always can't achieve ...
Generic Graphical User Interface for CBIR Framework
AbstractContent-based image retrieval system (CBIR) is a well-known and widely used system for image retrieval. Most of the current CBIR systems are either command-based or specific to applications. However, due to the availability of a good computing ...
Comments