An effective solution for trademark image retrieval by combining shape description and feature matching. (English) Zbl 1192.68232

Qi, Heng; Li, Keqiu; Shen, Yanming; Qu, Wenyu

Pattern Recognition 43, No. 6, 2017-2027 (2010).

Summary: Trademark image retrieval (TIR), a branch of content-based image retrieval (CBIR), is playing an important role in multimedia information retrieval. This paper proposes an effective solution for TIR by combining shape description and feature matching. We first present an effective shape description method which includes two shape descriptors. Second, we propose an effective feature matching strategy to compute the dissimilarity value between the feature vectors extracted from images. Finally, we combine the shape description method and the feature matching strategy to realize our solution. We conduct a large number of experiments on a standard image set to evaluate our solution and the existing solutions. By comparison of their experimental results, we can see that the proposed solution outperforms existing solutions for the widely used performance metrics.

MSC:

68P20	Information storage and retrieval of data
68T10	Pattern recognition, speech recognition
68U10	Computing methodologies for image processing

Keywords:

content-based image retrieval; trademark image retrieval; shape description; feature matching

References:

[1]	Arnold, W.M.; Worring, M.; Santini, S.; Gupta, A.; Jain, R., Content-based image retrieval at the end of the early years, IEEE transactions on pattern analysis and machine intelligence, 22, 12, 38-45, (2000)
[2]	Lew, M.S.; Sebe, N.; Djeraba, C.; Jain, R., Content-based multimedia information retrieval: state of the art and challenges, ACM transactions on multimedia computing, communications, and applications, 2, 1-19, (2006)
[3]	J. Schietse, J.P. Eakins, R.C. Veltkamp, Practice and challenges in trademark image retrieval, in: CIVR’07, 2007.
[4]	Yin, P.Y.; Yeh, C.C., Content-based retrieval from trademark databases, Pattern recognition letters, 23, 113-126, (2002) · Zbl 0994.68515
[5]	Jain, A.K.; Vailaya, A., Shape-based retrieval: a case study with trademark image database, Pattern recognition, 31, 1369-1390, (1998)
[6]	Wei, C.H., Trademark image retrieval using synthetic features for describing global shape and interior structure, Pattern recognition, 42, 386-394, (2008) · Zbl 1181.68259
[7]	Zhang, D.; Lu, G., Review of shape representation and description techniques, Pattern recognition, 37, 1-19, (2004)
[8]	D. Zhang, G. Lu, A comparative study of Fourier descriptors for shape representation and retrieval, in: The 5th Asian Conference on Computer Vision (ACCV02), 2002.
[9]	Jain, A.K.; Vailaya, A., Image retrieval using color and shape, Pattern recognition, 29, 1233-1244, (1996)
[10]	Wang, Y.P.; Lee, K.T.; Toraichi, K., Multiscale curvature-based shape representation using B-spline wavelets, IEEE transactions on image processing, 8, 1586-1592, (1999)
[11]	Alajlan, N.; Rube, I.E.; Kamel, M.S.; Freeman, G., Shape retrieval using triangle-area representation and dynamic space warping, Pattern recognition, 40, 1911-1920, (2007) · Zbl 1120.68046
[12]	Eakins, J.P.; Boardman, J.M.; Graham, M.E., Similarity retrieval of trademark images, IEEE multimedia, 5, 53-63, (1998)
[13]	Dudani, S.A.; Breeding, K.J.; McGhee, R.B., Aircraft identification by moment invariants, IEEE transactions on computers, 26, 39-45, (1977)
[14]	G. Taubin, D.B. Cooper, Recognition and positioning of rigid objects using algebraic moment invariants, in: SPIE Conference on Geometric Methods in Computer Vision, 1991.
[15]	Teh, C.H.; Chin, R.T., On image analysis by the methods of moments, IEEE transactions on pattern analysis and machine intelligence, 10, 496-513, (1991) · Zbl 0709.94543
[16]	Wee, C.Y.; Paramesran, R., On the computational aspects of Zernike moments, Image and vision computing, 25, 967-980, (2007)
[17]	Papacostas, G.A.; Boutalis, Y.S.; Karras, D.A.; Mertzios, B.G., A new class of Zernike moments for computer vision applications, Information sciences, 177, 2802-2819, (2007) · Zbl 1116.68103
[18]	Chong, C.W.; Raveendran, P.; Mukundan, R., A comparative analysis of algorithms for fast computation of Zernike moments, Pattern recognition, 36, 731-742, (2003) · Zbl 1028.68142
[19]	Gu, J.; Shu, H.Z.; Toumoulin, C.; Luo, L.M., A novel algorithm for fast computation of Zernike moments, Pattern recognition, 35, 2905-2911, (2002) · Zbl 1010.68147
[20]	J. Wang, H. Zha, R. Cipolla, Combining interest points and edges for content-based image retrieval, in: IEEE International Conference on Image Processing, 2005.
[21]	D. Unay, A. Ekin, R. Jasinschi, Medical image search and retrieval using local binary patterns and KLT feature points, in: IEEE International Conference on Image Processing, 2008.
[22]	J. Shi, C. Tomasi, Good features to track, in: IEEE Computer Vision and Pattern Recognition Conference, 1994.
[23]	Arevalillo-Herrez, M.; Domingo, J.; Ferri, F.J., Combining similarity measures in content-based image retrieval, Pattern recognition letters, 29, 2174-2181, (2008)
[24]	\(\langle\)http://www.mip.sdu.dk/ipl98/〉.
[25]	\(\langle\)http://www.lsus.edu/faculty/∼ecelebi/fourier.htm〉.
[26]	\(\langle\)http://www.ces.clemson.edu/∼stb/klt/index.html〉.