Skip to main content
Log in

RETRACTED ARTICLE: Fuzzy rough subset method with region based mining to improve the retrieval and ranking of real time images over larger image database

Multimedia Tools and Applications Aims and scope Submit manuscript

This article was retracted on 20 May 2023

This article has been updated

Abstract

Region based image mining is considered as an interesting approach that divides the images into several regions, where the features are extracted out from it and the set of features represents the contents of image from database. However, feature dimensionality and space complexity is one of the big issues in Image Retrieval Based on Content (CBIR). In this paper, fuzzy neighborhood rough subset method is used for feature reduction in an image. This helps to reduce the irrelevant features related to given query. The Support Vector Machine (SVM) is further used with fuzzy rough subset method to classify the images related to given query. This extracts well the spectral data characteristics between the query and database images. Performance of proposed fuzzy rough subset method with SVM classifier is tested against conventional methods. The results proves that the proposed method attains better classification of hyper spectral images than the other methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Change history

References

  1. Annrose J (2018) An efficient image retrieval system with structured query based feature selection and filtering initial level relevant images using range query. Optik-International Journal for Light and Electron Optics 157:1053–1064

    Article  Google Scholar 

  2. Arevalillo-Herráez M, Zacarés M, Benavent X, de Ves E (2008) A relevance feedback CBIR algorithm based on fuzzy sets. Signal Process Image Commun 23(7):490–504

    Article  Google Scholar 

  3. Benloucif S, Boucheham B (2014) Impact of feature selection on the performance of content-based image retrieval (CBIR). In: 2014 4th International Symposium ISKO-Maghreb: Concepts and Tools for knowledge Management (ISKO-Maghreb). IEEE, p 1–7

  4. Bugatti PH, Ribeiro MX, Traina AJ, Traina Jr C (2011) Feature selection guided by perception in medical CBIR systems. In: 2011 First IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB). IEEE, p 323–330

  5. Chandra I, Sivakumar N, Gokulnath CB, Parthasarathy P (2018) IoT based fall detection and ambient assisted system for the elderly. Clust Comput 1–9

  6. Chen Y, Lan Y, Ren H (2012) A feature selection method base on ga for cbir mammography cad. In: 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), Vol. 2. IEEE, p 175–178

  7. Choi JY, Kim DH, Plataniotis KN, Ro YM (2016) Classifier ensemble generation and selection with multiple feature representations for classification applications in computer-aided detection and diagnosis on mammography. Expert Syst Appl 46:106–121

    Article  Google Scholar 

  8. Da Silva SF, Ribeiro MX, Neto JDEB, Traina-Jr C, Traina AJ (2011) Improving the ranking quality of medical image retrieval using a genetic feature selection method. Decis Support Syst 51(4):810–820

    Article  Google Scholar 

  9. Hilaire X, Jose J (2007) Enhancing CBIR through feature optimization, combination and selection. In: International Workshop on Content-Based Multimedia Indexing, 2007. CBMI’07. IEEE, p 267–274

  10. Hu Q, Yu D, Xie Z (2006) Information-preserving hybrid data reduction based on fuzzy-rough techniques. Pattern Recogn Lett 27(5):414–423

    Article  Google Scholar 

  11. Islam SM, Banerjee M, Bhattacharyya S, Chakraborty S (2017) Content-based image retrieval based on multiple extended fuzzy-rough framework. Appl Soft Comput 57:102–117

    Article  Google Scholar 

  12. Jensen R, Shen Q (2004) Fuzzy–rough attribute reduction with application to web categorization. Fuzzy Sets Syst 141(3):469–485

    Article  MathSciNet  MATH  Google Scholar 

  13. Jin C, Jin SW (2015) Automatic image annotation using feature selection based on improving quantum particle swarm optimization. Signal Process 109:172–181

    Article  Google Scholar 

  14. Kanisha B, Lokesh S, Kumar PM, Parthasarathy P, Chandra Babu G (2018) Speech recognition with improved support vector machine using dual classifiers and cross fitness validation. Pers Ubiquit Comput 1–9

  15. Korn F, Pagel BU, Faloutsos C (2001) On the “dimensionality curse” and the “self-similarity blessing”. IEEE Trans Knowl Data Eng 13(1):96–111

    Article  Google Scholar 

  16. Kumar PM, Lokesh S, Varatharajan R, Babu GC, Parthasarathy P (2018) Cloud and IoT based disease prediction and diagnosis system for healthcare using fuzzy neural classifier. Futur Gener Comput Syst 86:527–534

    Article  Google Scholar 

  17. Kumar PM, Devi U, Manogaran G, Sundarasekar R, Chilamkurti N, Varatharajan R (2018) Ant colony optimization algorithm with internet of vehicles for intelligent traffic control system. Comput Netw 144:154–162

    Article  Google Scholar 

  18. Lin WC, Oakes M, Tait J (2010) Improving image annotation via representative feature vector selection. Neurocomputing 73(10):1774–1782

    Article  Google Scholar 

  19. Lokesh S, Kumar PM, Devi MR, Parthasarathy P, Gokulnath C (2018) An automatic Tamil speech recognition system by using bidirectional recurrent neural network with self-organizing map. Neural Comput & Applic 1–11

  20. Mathan K, Kumar PM, Panchatcharam P, Manogaran G, Varadharajan R (2018) A novel Gini index decision tree data mining method with neural network classifiers for prediction of heart disease. Des Autom Embed Syst 1–18

  21. Mosbah M, Boucheham B (2017) Distance selection based on relevance feedback in the context of CBIR using the SFS meta-heuristic with one round. Egyptian Informatics Journal 18(1):1–9

    Article  Google Scholar 

  22. Padmavathy TV, Vimalkumar MN, Nagarajan S, Babu GC, Parthasarathy P (2018) Performance analysis of pre-cancerous mammographic image enhancement feature using non-subsampled shearlet transform. Multimed Tools Appl 1–16

  23. Parthasarathy P, Vivekanandan S (2018) A comprehensive review on thin film-based nano-biosensor for uric acid determination: arthritis diagnosis. World Review of Science, Technology and Sustainable Development 14(1):52–71

    Article  Google Scholar 

  24. Parthasarathy P, Vivekanandan S (2018) Urate crystal deposition, prevention and various diagnosis techniques of GOUT arthritis disease: a comprehensive review. Health Information Science and Systems 6(1):19

    Article  Google Scholar 

  25. Parthasarathy P, Vivekanandan S (2018) A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases. Informatics in Medicine Unlocked

  26. Parthasarathy P, Vivekanandan S (2018) A typical IoT architecture-based regular monitoring of arthritis disease using time wrapping algorithm. Int J Comput Appl 1–11

  27. Priya S, Varatharajan R, Manogaran G, Sundarasekar R, Kumar PM (2018) Paillier homomorphic cryptosystem with poker shuffling transformation based water marking method for the secured transmission of digital medical images. Pers Ubiquit Comput 1–11

  28. Rashedi E, Nezamabadi-Pour H (2012) Improving the precision of CBIR systems by feature selection using binary gravitational search algorithm. In: 2012 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP). IEEE, p 039–042

  29. Rashedi E, Nezamabadi-Pour H, Saryazdi S (2013) A simultaneous feature adaptation and feature selection method for content-based image retrieval systems. Knowl-Based Syst 39:85–94

    Article  Google Scholar 

  30. Rashno A, Sadri S (2017) Content-based image retrieval with color and texture features in neutrosophic domain. In: 2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA). IEEE, p 50–55

  31. Sundarasekar R, Thanjaivadivel M, Manogaran G, Kumar PM, Varatharajan R, Chilamkurti N, Hsu CH (2018) Internet of things with maximal overlap discrete wavelet transform for remote health monitoring of abnormal ECG signals. J Med Syst 42(11):228

    Article  Google Scholar 

  32. Varadharajan R, Priyan MK, Panchatcharam P, Vivekanandan S, Gunasekaran M (2018) A new approach for prediction of lung carcinoma using back propagation neural network with decision tree classifiers. J Ambient Intell Humaniz Comput 1–12

  33. Vijayakumar V, Priyan MK, Ushadevi G, Varatharajan R, Manogaran G, Tarare PV (2018) E-health cloud security using timing enabled proxy re-encryption. Mobile Networks and Applications 1–12

  34. Wang Y, Cen Y, Zhao R, Cen Y, Hu S, Voronin V, Wang H (2017) Separable vocabulary and feature fusion for image retrieval based on sparse representation. Neurocomputing 236:14–22

    Article  Google Scholar 

  35. Xu F, Zhang YJ (2007) Integrated patch model: a generative model for image categorization based on feature selection. Pattern Recogn Lett 28(12):1581–1591

    Article  Google Scholar 

  36. Yuan L, Liu J, Tang X (2014) Combining example selection with instance selection to speed up multiple-instance learning. Neurocomputing 129:504–515

    Article  Google Scholar 

  37. Zhao T, Lu J, Zhang Y, Xiao Q (2008) Feature selection based on genetic algorithm for cbir. In: Congress on Image and Signal Processing, 2008. CISP’08, Vol. 2. IEEE, p 495–499

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Venkatasalam.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s11042-023-15835-7

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Venkatasalam, K., Rjendran, P. & Thangavel, M. RETRACTED ARTICLE: Fuzzy rough subset method with region based mining to improve the retrieval and ranking of real time images over larger image database. Multimed Tools Appl 79, 3861–3878 (2020). https://doi.org/10.1007/s11042-019-7289-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-7289-x

Keywords

Navigation