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A hybrid approach for Content-Based Image Retrieval based on Fast Beta Wavelet network and fuzzy decision support system

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Abstract

Content-based image retrieval (CBIR) has been a worthwhile topic for research for several years. A powerful CBIR system should minimize the semantic gap between the low-level features and high-level concepts in order to satisfy users requirements. Moreover, it should take into consideration the execution time. In this paper, we present a new semantic approach for CBIR supported by a parallel aggregation of content-based features extraction (shape, texture, color) using fuzzy support decision mechanisms. Shape features are based on Fast Beta Wavelet Network modeling and Hue moments. The texture descriptor is based on Energy computing at different decomposition levels. Finally, we present an implementation of a new color feature extraction based on fuzzy indexed color map. In the second stage, we propose a Fuzzy Decision Support System for feature (shape, texture, color) aggregation to improve the retrieval performance. The proposed approach is tested on four most popular datasets: Wang, INRIA Holidays, UKBench and samples from ImageNet, and the experiments showed that the proposed approach can achieve a satisfactory retrieval performance with an acceptable search time.

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Notes

  1. Available at: http://wang.ist.psu.edu/docs/related/.

  2. Available at: http://lear.inrialpes.fr/~jegou/data.php#holidays.

  3. Available at: http://www.vis.uky.edu/~stewe/ukbench/.

  4. Available at: http://www.image-net.org/.

  5. http://www.image-net.org/synset?wnid=n02084071.

References

  1. Zaied, M., Amar, C.B., Alimi, M. A.: Award a new wavelet based beta function. In: International Conference on Signal, System and Design, SSD03, Tunisia, pp. 185–191 (2003)

  2. Amar, C.B., Zaied, M., Alimi, M.A.: Beta wavelets: synthesis and application to lossy image compression. Adv. Eng. Softw. 36(7), 459–474 (2005)

  3. Zaied, M., Said, S., Jemai, O., Amar, C.: A novel approach for face recognition based on fast learning algorithm and wavelet network theory. Int. J. Wavelets Multiresolut. Inf. Process. 19, 923–945 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  4. Zaied, M., Amar, C., Alimi, M.A.: Beta wavelet networks for face recognition. J. Decis. Syst. 14, 109–122 (2005)

    Article  MATH  Google Scholar 

  5. Said, S., Amor, B.B., Zaied, M., Amar, C.B., Daoudi, M.: Fast and efficient 3D face recognition using wavelet networks. In: 16th IEEE International Conference on Image Processing, Cairo, Egypt, pp. 4153–4156 (2009)

  6. Jemai, O., Zaied, M., Amar, C.B.: Fast learning algorithm of wavelet network based on fast wavelet transform. Int. J. Pattern Recogn. Artif. Intell. 25(8), 1297–1319 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  7. Jemai, O., Zaied, M., Amar, C.B., Alimi, A.: Pyramidal hybrid approach. Int. J. Wavelets Multiresolut. Inf. Process. 9, 111–130 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  8. Ejbali, R., Benayed, Y., Zaied, M., Alimi, A.: Wavelet networks for phonemes recognition. In: International Conference on Systems and Information Processing (2009)

  9. Ejbali, R., Zaied, M., Amar, C.B.: Multi-input multi-output beta wavelet network: modeling of acoustic units for speech recognition. In: International Journal of Advanced Computer Science and Applications (IJACSA), The Science and Information Organization(SAI), Vol. 3 (2012)

  10. Ejbali, R., Zaied, M., Amar, C.B.: Wavelet network for recognition system of Arabic word. Int. J. Speech Technol. 13, 163–174 (2010)

  11. Bouchrika, T., Zaied, M., Jemai, O., Amar, C.B.: Ordering computers by hand gestures recognition based on wavelet networks. In: International Conference on Communications, Computing and Control Applications (CCCA), Marseilles, pp. 36–41 (2012)

  12. Madhu, S.: Content based image retrieval: a quantitative comparison between query by color and query by texture. J. Ind. Intell. Inf. 2(2), 108–112 (2014)

    Google Scholar 

  13. Howarth, P., Rger, S.: Evaluation of texture features for content-based image retrieval. In: International Conference on Image and Video Retrieval, pp. 326–334 (2004)

  14. Sarker, I.H., Iqbal, S.: Content-based image retrieval using Haar wavelet transform and color moment. Smart Comput. Rev. 3, (3) (2013)

  15. Bhute, A. N., Meshram, B. B.: Content based image indexing and retrieval. Int. J. Graph. Image Process. 3(4), 235–246 (2013)

  16. Xu, J., Wu, D.: Ripplet-II transform for feature extraction. In: Proceedings of SPIE 7744, Visual Communications and Image Processing, China (2010)

  17. Xu, J., Wu, D.: Ripplet transform type II transform for feature extraction. IET Image Proc. 6(4), 374385 (2012)

    Article  MathSciNet  Google Scholar 

  18. Lamard, M., Cazuguel, G., Quellec, G., Bekri, L., Roux, C., Cochener, B.: Content based image retrieval based on wavelet transform coefficients distribution. In: Conference Proceedings : Annual International Conference of the IEEE Engineering, Lyon, pp. 4532–4535 (2007)

  19. Jalab, H. A.: Image retrieval system based on color layout descriptor and Gabor filters. In: IEEE Conference on Open Systems (ICOS), Langkawi, pp. 32–36 (2011)

  20. Rao, M.B., Rao, B.P., Govardhan, A.: CTDCIRS: content based image retrieval system based on dominant color and texture features. Int. J. Comput. Appl. 18(6), 40–46 (2011)

    Google Scholar 

  21. Prabhu, J., Kumar, J.S.: Wavelet based content based image retrieval using color and texture feature extraction by gray level cooccurence matrix and color cooccurence matrix. J. Comput. Sci. 10(1), 15–22 (2014)

    Article  Google Scholar 

  22. Saad, M.H., Saleh, H.I., Konbor, H., Ashour, M.: Image retrieval based on integration between \(YC_bC_r\) color histogram and texture feature. Int. J. Comput Theory Eng. 3(5), 701–706 (2011)

  23. Rao, M.B., Rao, B.P., Govardhan, A.: Content based image retrieval using dominant color, texture and shape. Int. J. Eng. Sci. Technol. 3(4), 2887–2896 (2011)

    Article  Google Scholar 

  24. Lande, M.V., Bhanodiya, P., Jain, P.: An effective content-based image retrieval using color texture and shape feature. Adv. Intell. Syst. Comput. 243, 1163–1170 (2014)

    Article  Google Scholar 

  25. Hiremath, P.S., Pujari, J.: Content based image retrieval based on color, texture and shape features using image and its complement. Int. J. Comput. Sci. Secur. 1(4), 25–35 (2007)

    Google Scholar 

  26. Kumar, D.A., Esther, J.: Comparative study on CBIR based by color histogram, gabor and wavelet transform. Int. J. Comput. Appl. 17(3), 37–44 (2011)

    Google Scholar 

  27. Atlam, H.F., Attiya, G., El-Fishawy, N.: Comparative study on CBIR based by color feature, gabor and wavelet transform. Int. J. Comput. Appl. 78(16), 9–15 (2013)

    Google Scholar 

  28. Banerjee, M., Kundu, M.K., Maji, P.: Content-based image retrieval using visually significant point features. Fuzzy Sets Syst. 160, 33233341 (2009)

    Article  MathSciNet  Google Scholar 

  29. Choudhary, R., Raina, N., Chaudhary, N., Chauhan, R., Goudar, R. H.: An Integrated approach to content based image retrieval. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI), New Delhi, September, pp. 2404–2410 (2014)

  30. John, D., Tharani, S.T., Sreekumar, K.: Content based image retreival using HSV-color histogram and GLCM. Int. J. Adv. Res. Comput. Sci. Manag. Studi. 2(1), 246–253 (2014)

    Google Scholar 

  31. Jhanwar, N., Chaudhuri, S., Seetharaman, G., Zavidovique, B.: Content based image retrieval using motif cooccurrence matrix. Image Vis. Comput. 22, 12111220 (2004)

    Article  Google Scholar 

  32. Wang, X.-Y., Yu, Y.-J., Yang, H.-Y.: An effective image retrieval scheme using color, texture and shape features. Comput. Stand. Interfaces 33, 5968 (2011)

    Article  Google Scholar 

  33. Region based image retrieval using Shape-Adaptive DCT, signal and information processing (ChinaSIP). In: IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP), July, Xian, pp. 470–474 (2014)

  34. Madhu, S.: Content based Image retrieval: a quantitative comparison between query by color and query by texture. J. Ind. Intell. Inf. 2(2), 108–112 (2014)

    Google Scholar 

  35. Alzghool, M., Inkpen, D.: A novel class-based data fusion technique for information retrieval. J. Emerg. Technol. Web Intell. 2(3), 160–166 (2010)

    Google Scholar 

  36. Chatzichristos, S. A., Arampatzis, A., Boutalis, Y. S.: Investigating the behavior of compact composite descriptors in early fusion, late fusion and distributed image retrieval. Radioengineering 19(4), 725–733 (2010)

  37. Jovic, M., Hatakeyama, Y., Dong, F., Hirota, K.: Image retrieval based on similarity score fusion from feature similarity ranking lists. In: Lecture Notes in Computer Science, Vol. 4223, pp. 461–470 (2006)

  38. Wenger, C., Douze, M., Jgou, H.: Bag-of-colors for improved image search. In: The 19th ACM International Conference on Multimedia, Scottsdale, November (2011)

  39. Liu, Z., Wang, S., Zheng, L., Tian, Q.: Visual reranking with improved image graph. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May, pp. 6889–3893 (2014)

  40. Zheng, L., Wang, S.: Coupled binary embedding for large-scale image retrieval. IEEE Trans. Image Process. 23(8), 3368–3380 (2014)

    Article  MathSciNet  Google Scholar 

  41. de Weijer, J. V., Schmid, C., Verbeek, J., Larlus, D.: Learning color names for realworld applications. In: IEEE TIP (2009)

  42. Zheng, L., Wang, S., Liu, Z., Tian, Q.: Packing and padding: coupled multi-index for accurate image retrieval. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June, Columbus, pp. 1947–1954 (2014)

  43. Jain, M., Jgou, H., Gros, P.: Asymmetric hamming embedding: Taking the best of our bits for large scale image search. In: Proceedings of ACM Multimedia, pp. 1441–1444 (2011)

  44. Deng, C., Ji, R., Liu, W., Tao, D., Gao, X.: Visual reranking through weakly supervised multi-graph learning. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 2600–2607 (2013)

  45. Shen, X., Lin, Z., Brandt, J., Avidan, S., Wu, Y.: Object retrieval and localization with spatially-constrained similarity measure and k-NN reranking. In: Proceedings on Computer Vision and Pattern Recognition (CVPR), June, pp. 3013–3020 (2012)

  46. Jgou, H., Douze, M., Schmid, C.: Improving bag-of-features for large scale image search. Int. J. Comput. Vision 87(3), 316–336 (2010)

    Article  Google Scholar 

  47. Wengert, C., Douze, M., Jgou, H.: Bag-of-colors for improved image search. In: Proceedings of 19th ACM Multimedia, pp. 1437–1440 (2011)

  48. Jegou, H., Schmid, C., Harzallah, H., Verbeek, J.: Accurate image search using the contextual dissimilarity measure. IEEE Trans. Pattern Anal. Mach. Intell. 32(1), 2–11 (2010)

    Article  Google Scholar 

  49. Zhang, S., Yang, M., Cour, T., Yu, K., Metaxas, D. N.: Query specific fusion for image retrieval. In: 12th European Conference on Computer Vision, October, pp. 660–673 (2012)

  50. Madugunki, M., Bormane, D.S., Bhadoria, S., Dethe, C. G.: Comparison of different CBIR techniques. In: 3rd International Conference on Electronics Computer Technology (ICECT), Kanyakumari, pp. 372–375 (2011)

  51. Mejdoub, M., Amar, C.B.: Classification improvement of local feature vectors over the KNN algorithm. Multimedia Tools Appl. 64(1), 197–218 (2013)

    Article  Google Scholar 

  52. Mejdoub, M., Fonteles, L., Amar, C.B., Antonini, M.: Embedded lattices tree: an efficient indexing scheme for content based retrieval on image databases. J. Vis. Commun. Image Represent. 20(2), 145–156 (2009)

    Article  Google Scholar 

  53. Dammak, M., Mejdoub, M., Zaied, M., Amar, C.B.: Feature vector approximation based on wavelet network. In: ICAART 2012—Proceedings of the 4th International Conference on Agents and Artificial Intelligence, pp. 394–399 (2012)

  54. Othmani, M., Bellil, W., Amar, C.B., Alimi, A.M.: A new structure and training procedure for multi-mother wavelet networks. Int. J. Wavelets Multiresolut. Inf. Process. 8(1), 149–175 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  55. El’Arbi, M., Amar, C.B., Nicolas, H. Video watermarking based on neural networks. In: IEEE International Conference on Multimedia and Expo, ICME 2006—Proceedings, art. no. 4036915, pp. 1577–1580 (2006)

  56. Mejdoub, M., Fonteles, L., BenAmar, C., Antonini, M.: Fast indexing method for image retrieval using tree-structured lattices. In: International Workshop on Content-Based Multimedia Indexing, CBMI 2008. Conference Proceedings, art. 4564970, pp. 365–372 (2008)

  57. Boughrara, H., Chtourou, M., Amar, C.B.: MLP neural network based face recognition system using constructive training algorithm. In: Proceedings of 2012 International Conference on Multimedia Computing and Systems, ICMCS 2012, art. no. 6320263, pp. 233–238 (2012)

  58. Mejdoub, M., Fonteles, L., Amar, C.B, Antonini, M.: Fast algorithm for image database indexing based on lattice. In: European Signal Processing Conference, pp. 1799–1803 (2007)

  59. Gosselin, P.H., Cord, M.: Active learning methods for interactive image retrieval. IEEE Trans. Image Process. 17(7), 1200–1211 (2008)

    Article  MathSciNet  Google Scholar 

  60. Rajput, E., Kang, H.S.: Content based Image retrieval by using the Bayesian algorithm to improve and reduce the noise from an image. Global J. Comput. Sci. Technol. Graph. Vision 13(6), 12–16 (2013)

    Google Scholar 

  61. Zhao, T., Lu, J., Zhang, Y., Xiao, Q.: Feature selection based-on genetic algorithm for CBIR. In: Congress on Image and Signal Processing, Sanya, pp. 495–499 (2008)

  62. Liu, M.-S., Li, J.-H., Liu, H.: Image retrieval technology of multi-MPEG-7 features based on genetic algorithm. In: Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, pp. 19–22 (2007)

  63. Belattar, K., Mostefai, S.: CBIR with RF: which Technique for which image. In: 3rd International Symposium ISKO-Maghreb, pp. 1–7 (2013)

  64. Shanmugapriya, N., Nallusamy, R.: A new content based image retrieval system using GMM and relevance feedback. J. Comput. Sci. 10(2), 330–340 (2014)

    Article  Google Scholar 

  65. Chowdhury, M., Das, S., Kundu, M.K.: Interactive content based image retrieval using Ripplet Transform and fuzzy relevance feedback. In: Proceedings of the First Indo-Japan Conference on Perception and Machine Intelligence (PerMIn’12), pp. 243–251 (2012)

  66. Yasmin, M., Mohsin, S., Irum, I., Sharif, M.: Content based image retrieval by shape. Color and relevance feedback. Life Sci. J 10(4), 593–598 (2013)

    Google Scholar 

  67. Belattar, K., Mostefai, S.: CBIR using relevance feedback:comparative analysis and major challenges. In: 5th International Conference on Computer Science and Information Technology (CSIT), pp. 317–325 (2013)

  68. Yasmin, M., Sharif, M., Mohsin, S.: Use of Low Level Features for Content Based Image Retrieval: Survey. Research Journal of Recent Sciences 2(11), 65–75 (2013)

    Google Scholar 

  69. Verma, B., Kulkarni, S.: A fuzzy-neural approach for interpretation and fusion of colour and texture features for CBIR systems. Appl. Soft Comput. 5, 119130 (2004)

    Article  Google Scholar 

  70. Sriramakrishnan, C., Shanmugam, A.: An fuzzy neural approach for medical image retrieval. J. Comput. Sci. 8(11), 1809–1813 (2012)

  71. Syam, B., Victor, J.S.R., Srinivasa Rao, Y.: Efficient similarity measure via genetic algorithm for content based medical image retrieval with extensive features. In: International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), Kottayam, pp. 704–711(2013)

  72. Bagheri, B., Pourmahyabadi, M., Nezamabadi-pour, H.: A novel content based image retrieval approach by fusion of short term learning methods. In: 5th Conference on Information and Knowledge Technology (IKT), pp. 355–358 (2013)

  73. Rashedi, E., Nezamabadi-pour, H., Saryazdi, S.: A Gradient Descent based Similarity Refinement Method for CBIR Systems, Tehran (2012)

  74. Tong, S., Chang, E.: Support Vector Machine Active Learning for Image Retrieval. In: The ninth ACM International Conference on Multimedia, pp. 107–118 (2001)

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Acknowledgments

The authors would like to acknowledge the financial support of this work by grants from General Direction of Scientific Research (DGRST), Tunisia, under the ARUB program.

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Authors and Affiliations

  1. National School of Engineers, Gabes, Tunisia

    Asma ElAdel & Mourad Zaied

  2. Faculty of Sciences, Gabes, Tunisia

    Ridha Ejbali

  3. National School of Engineers, Sfax, Tunisia

    Chokri Ben Amar

  4. Research Group in Intelligent Machines, National School of Engineers of Sfax, B.P. 1173, Sfax, Tunisia

    Chokri Ben Amar

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  1. Asma ElAdel
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  2. Ridha Ejbali
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Correspondence to Asma ElAdel.

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ElAdel, A., Ejbali, R., Zaied, M. et al. A hybrid approach for Content-Based Image Retrieval based on Fast Beta Wavelet network and fuzzy decision support system. Machine Vision and Applications 27, 781–799 (2016). https://doi.org/10.1007/s00138-016-0789-z

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