A survey on content based image retrieval

Aus de_evolutionary_art_org
Wechseln zu: Navigation, Suche


T. Dharani and I. Aroquiaraj: A survey on content based image retrieval. Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 International Conference, pp. 485-490




Literature survey is most important for understanding and gaining much more knowledge about specific area of a subject. In this paper a survey on content based image retrieval presented. Content Based Image Retrieval (CBIR) is a technique which uses visual features of image such as color, shape, texture, etc... to search user required image from large image database according to user's requests in the form of a query image. We consider Content Based Image Retrieval viz. labelled and unlabelled images for analyzing efficient image for different image retrieval process viz. D-EM, SVM, RF, etc. To determining the efficient imaging for Content Based Image Retrieval, We performance literature review by using principles of Content Based Image Retrieval based unlabelled images. And also give some recommendations for improve the CBIR system using unlabelled images.

Extended Abstract


author={T. Dharani and I. L. Aroquiaraj},
booktitle={Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 International Conference on},
title={A survey on content based image retrieval},
keywords={content-based retrieval;image retrieval;visual databases;CBIR system;RF;SVM;content based image retrieval;query image database;unlabelled image;Image retrieval;Pattern recognition;Radio frequency;Supervised learning;Support vector machines;Active Learning;CBIR;RF;SVM;Unlabelled images},
url={http://dx.doi.org/10.1109/ICPRIME.2013.6496719 http://de.evo-art.org/index.php?title=A_survey_on_content_based_image_retrieval },

Used References

R. Anderson, "A spreading activation theory of memory," Verbal Learning and Verbal Behavior, 1983, 22: 261-295. http://dx.doi.org/10.1016/S0022-5371(83)90201-3

Bart Thomee, Michael S. Lew, "Relevance Feedback in Content-Based Image Retrieval: Promising Directions".

I.J. Cox, et al., "The Bayesian image retrieval system, PicHunter: theory, implementation, and psychophysical experiments." IEEE Trans. On Image Processing. 9. (1)2000 p. 20-37. http://dx.doi.org/10.1109/83.817596

Cohen, N. Sebe, F. G. Cozman, M. C. Cirelo, and T. S. Huang, "Semi-supervised learning of classifiers: theory and algorithms for Bayesian network classifiers and applications to human-computer interaction," submitted to IEEE Trans. on PAMI, in revision, 2003.

Chapelle, P. Haffner, and V. Vapnik. "Svms for histogram based image classification."IEEE Transactions on NeuralNetworks, 9, 1999.

Campbell. "Algorithmic approaches to training support vector machines: A survey." In ESANN, pages 27-36. D-Facto Publications, 2000.

Dan Zhang, Zhenwei Shi, Yangqiu Song, and Changshui Zhang. "Localized Content-Based Image Retrieval UsingSemi-Supervised Multiple Instance Learning."Y. Yagi et al. (Eds.): ACCV 2007, Part I, LNCS 4843, pp. 180-188,@ Springer-Verlag Berlin Heidelberg (2007).

Dong, A. and Bhanu, B. 2003. "A new semi-supervised EM algorithm for image retrieval." In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition.Madison, WI, 662{667. http://dx.doi.org/10.1109/CVPR.2003.1211530

G. Das and S. Ray. "A comparison of relevance feed-back strategies in CBIR," IEEE, 2007. http://dx.doi.org/10.1109/ICIS.2007.12

Goldman, S., Zhou, Y. "Enhancing supervised learning with unlabelled data."In:Proceedings of the 17th International Conference on Machine Learning, San Francisco, CA (2000) 327-334.

Y.Wu, T.S.Huang, "Using Unlabelled Data in Supervised Learning by Discriminant-EM Algorithm",NIPS99 Workshop on Using Unlabelled Data in Supervised Learning, Colorado, 1999.

Jain and A.Vailaya, "Image Retrieval Using Color and Shape,"Pattern Recognit., Vol. 29, No. 8, pp. 1233-1244, Aug. 1996. http://dx.doi.org/10.1016/0031-3203(95)00160-3

JormaLaaksonen, Markus Koskela, Sami Laakso, ErkkiOja. "PicSOM-Content Based Image Retrieval with Self Organizing Maps." Pattern Recognition Letters 21 (2000) 1199-1207. http://dx.doi.org/10.1016/S0167-8655(00)00082-9

Jingrui He, Mingjing Li, Hong-Jiang Zhang, Hanghang Tong, Changshui Zhang. "Manifold-Ranking Based Image Retrieval."MM'04, NEW YORK, NEW YORK, USA. Copyright 2004 ACM 1-58113-893-8/04/0010(OCTOBER 10-16, 2004). http://dx.doi.org/10.1145/1027527.1027531

Koikkalainen, P., Oja, E., 1990. "Self-organizing hierarchical feature maps." In: Proceedings of 1990 International Joint Conference on Neural Networks, Vol. II. IEEE, INNS, San Diego, CA. http://dx.doi.org/10.1109/IJCNN.1990.137727

LixinDuan, Ivor W. Tsang, and Dong Xu, "Domain transfer multiple kernel learning," IEEE Transactions on Pattern Analysis and MachineIntelligence, vol. 34, no. 3, pp. 465-479, march 2012. http://dx.doi.org/10.1109/TPAMI.2011.114

Zhang, L., Lin, F., and Zhang, B. "Support vector machine learning for image retrieval."Proc. IEEE Int. Conf. on ImageProcessing, vol. 2, pp. 721-724, 2001. http://dx.doi.org/10.1109/ICIP.2001.958595

Lei Wang, KapLuk Chan, Zhihua Zhang, "Bootstrapping SVM Active Learning by Incorporating Unlabelled Images for Image Retrieval." Lining Zhang, Student Member, IEEE, Lipo Wang, Senior Member, IEEE, and Weisi Lin, Senior Member, IEEE. "Conjunctive Patches Subspace Learning with Side Information for Collaborative Image Retrieval." http://dx.doi.org/10.1109/CVPR.2003.1211412

MehwishRehman, Muhammad Iqbal, Muhammad Sharif and MudassarRaza. "Content Based Image Retrieval: Survey."DOI: 10.5829/idosi.wasj.2012. 19.03.1506, World Applied Sciences Journal 19 (3): 404-412, 2012, ISSN 1818-4952; IDOSI Publications, 2012.

Manjunath, B.S., and Ma, W.Y. "Texture features for browsing and retrieval of image data."IEEE Trans. OnPattern Analysis and Machine Intelligence, vol. 18, pp. 837-842, 1996. http://dx.doi.org/10.1109/34.531803

C. Nastar, M. Mitschke and C. Meilhac "Efficient Query Refinement for Image Retrieval", IEEE Conf. Computer Vision and Pattern Recognition CVPR'98, Santa Barbara, CA, June 1998. http://dx.doi.org/10.1109/CVPR.1998.698659

K. Nigam, A McCallum, S. Thrun, and T. Mitchell, "Text classification from labelled and unlabelled documents using EM," Machine Learning, 39, pp.1-32, 2000. http://dx.doi.org/10.1023/A:1007692713085

Philippe H. Gosselin, Matthieu Cord. "A Comparison of Active Classification Methods for Content-Based Image Retrieval."Author manuscript, published in "International Workshop on Computer Vision meets Databases, ACM Sigmod, France (2004)". http://dx.doi.org/10.1145/1039470.1039483

Philippe H. Gosselin and Matthieu Cord. "Semantic kernel learning for interactive image retrieval". IEEE International Conference on Image Processing 2005, pp. I - 1177-80 . http://dx.doi.org/10.1109/ICIP.2005.1529966

Qi Tian, Jie Yu, Qing Xue, NicuSebe. "A New Analysis of the Value of Unlabelled Data in Semi-Supervised Learning for Image Retrieval."

T. Qin, X.D. Zhang, T.Y. Liu, D.S. Wang, W.Y. Ma, H.J. Zhang. "An active feedback framework for image retrieval," Pattern Recognition Letters, Volume 29, Is-sue 5, Pages 637-6461, April 2008. http://dx.doi.org/10.1016/j.patrec.2007.11.015

Y. Rui, T.S. Huang, M. Ortega, and S. Mehrotra, "Relevance feedback: a power tool for interactive content-based image retrieval," IEEETransactions on Circuits and Systems for Video Technology, vol. 8, no. 5, pp. 644-655, Sept. 1998. http://dx.doi.org/10.1109/76.718510

RitendraDatta, Jia Li, and James Z. Wang. "Content Based Image Retrieval Approaches and Trends of the new age." November 11-12, Singapore. ACM 1-59593-244-5/05/0011. 2005. http://dx.doi.org/10.1145/1101826.1101866

Songhao Zhu, Baoyun Wang, Yuncai Liu. "Spreading Activation Theory based image annotation." 978-1-4673-0046-9/12/IEEE 2012. http://dx.doi.org/10.1109/ICASSP.2012.6288064

Smith, J.R., Chang, S.-F., 1996. "VisualSEEk: a fully automated content-based image query system." In: Proceedings of the ACM Multimedia 1996. Boston, MA. http://dx.doi.org/10.1145/244130.244151

M. J. Swain and D. H. Ballard, "Color Indexing," International. Journal of Compututer Vision., Vol.7, No. 1, pp. 11-32, 1991. http://dx.doi.org/10.1007/BF00130487

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,no.12, pp. 1349-1380, Dec. 2000. http://dx.doi.org/10.1109/34.895972

B. M. Shahshahani, and D. A. Landgrebe, "The effect of unlabelled samples in reducing the small sample sizeproblem and mitigating the Hughes phenomenon," IEEE Trans. Geoscience and Remote Sensing, vol. 32, no. 5, pp.1087-1095, 1994. http://dx.doi.org/10.1109/36.312897

S. Tong, and E. Chang, "Support vector machine active learning for image retrieval," Proc. of ACM Int'l. Conf.Multimedia, pp. 107-118, 2001. http://dx.doi.org/10.1145/500156.500159

Thomas S. Huang, Xiang Sean Zhou, MunehiroNakazato, Ying Wu, Ira Cohen. "Learning in Content-Based Image Retrieval." http://dx.doi.org/10.1109/DEVLRN.2002.1011829

Wu, Y., Tian, Q., Huang, T.S. "Discriminant-EM algorithm with application to image retrieval." In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Hilton Head, SC (2000) 222-227. http://dx.doi.org/10.1109/CVPR.2000.855823

Tao Qin, Xu-Dong Zhang, Xu-Dong Zhang, De-Sheng Wang, Wei-Ying Ma, Hong-Jiang Zhang. "An active feedback framework for image retrieval."Elsevier 2007.

Tieu, K., and Viola, P. "Boosting image retrieval." Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 1,pp. 228-235, 2000. http://dx.doi.org/10.1109/CVPR.2000.855824

K. Tieu and P. Viola, "Boosting image retrieval," Int. J. Comput. Vis.,vol. 56, no. 1/2, pp. 17-36, 2004. http://dx.doi.org/10.1023/B:VISI.0000004830.93820.78

Wu, Y., Tian, Q., and Huang, T. "Discriminant-EM algorithm with application to image retrieval." Proc. IEEE Conf. onComputer Vision and Pattern Recognition, vol. 1, pp. 155-162, 2000. http://dx.doi.org/10.1109/CVPR.2000.855823

Y. Wu, Q. Tian, T. S. Huang, "Discriminant EM Algorithm with Application to Image Retrieval", IEEE Conf.Computer Vision and Pattern Recognition (CVPR)'2000, Hilton Head Island, South Carolina, June 13-15, 2000. http://dx.doi.org/10.1109/CVPR.2000.855823

Ulges, M. Worring, and T. Breuel. "Learning Visual Contexts for Image Annotation from Flickr Groups." IEEE Transactions on Multimedia, 2011, 13(2): 330-341. http://dx.doi.org/10.1109/TMM.2010.2101051

Y. Wu, Q. Tian, and T.S. Huang. "Discriminant EM algorithm with application to image retrieval," in proc.IEEEConf. Computer Vision and Pattern Recognition. South Carolina. June 2000. http://dx.doi.org/10.1109/CVPR.2000.855823

Xiaofei He, Deng Cai, and Jiawei Han, "Learning a maximum margin subspace for image retrieval," IEEE Transactions on Knowledge andData Engineering, vol. 20, no. 2, pp. 189-201, 2008. http://dx.doi.org/10.1109/TKDE.2007.190692

Yunqiang Chen, Xiang Zhou, and Thomas S. Huang. "ONECLASS SVM FOR LEARNING IN IMAGE RETRIEVAL." In Proc. IEEE Int'l Conf. on Image Processing, Thessaloniki, Greece (2001). http://dx.doi.org/10.1109/ICIP.2001.958946

Zhang, Lining.; Wang, Lipo.; Lin, Weisi. "Semi-Supervised Biased Maximum Margin Analysis for Interactive Image Retrieval." IEEE Transactions on Image Processing, 21(4), 2294-2308(2011). http://dx.doi.org/10.1109/TIP.2011.2177846

Zhi-Hua Zhou, Ke-Jia Chen, and Yuan Jiang. "Exploiting Unlabelled Data in Content-Based Image Retrieval."

X.S. Zhou and T.S. Huang. "Unifying keywords and contents for image retrieval," in proc. International Workshop on Content-Based Multimedia Indexing. Italy. Sept. 2001.

X.S. Zhou and T.S. Huang. "Exploring the nature andvariants of relevance feedback," in proc. IEEE Workshop onContent-based Access of Image and Video Libraries(CBAIVL), in conjunction with CVPR. Hawaii. Dec. 2001. http://dx.doi.org/10.1109/IVL.2001.990862

X. S. Zhou and T. S. Huang. "Small sample learning duringmultimedia retrieval using biasmap."Proceedings of IEEEInternational Conference on Computer Vision and PatternRecognition (CVPR), Hawaii, Dec, 2001. http://dx.doi.org/10.1109/CVPR.2001.990450


Full Text

internal file

Sonstige Links