Abstract
Due to the large volume of computational and storage requirements of content based image retrieval (CBIR), outsourcing image to cloud providers become an attractive research. Even though, the cloud service provides efficient indexing of the condensed images, it remains a major issue in the process of incremental indexing. Hence, an effective incremental indexing mechanism named Black Hole Entropic Fuzzy Clustering +Deep stacked incremental indexing (BHEFC+deep stacked incremental indexing) is proposed in this paper to perform incremental indexing through the retrieval of images. The images are encrypted and stored in cloud server for ensuring the security of image retrieval process. The trained images are clustered using the clustering mechanism BHEFC based on Tversky index. With the incremental indexing process, the new training images are encrypted and are converted into the decimal form such that the weight is computed using deep stacked auto-encoder that enable to update the centroid with new score values. The experimental evaluations on benchmark datasets shows that the proposed BHEFC+deep stacked incremental indexing model achieves better results compared to the existing methods by obtaining maximum accuracy of 96.728%, maximum F-measure of 83.598%, maximum precision of 84.447%, and maximum recall of 94.817%, respectively.
Similar content being viewed by others
References
Al Sibahee MA, Lu S, Abduljabbar ZA et al (2018) Efficient encrypted image retrieval in IoT-cloud with multi-user authentication. Int J Distrib Sens Networks:14. https://doi.org/10.1177/1550147718761814
Alsmadi MK (2020) Content-based image retrieval using color, shape and texture descriptors and features. Arab J Sci Eng 45:3317–3330. https://doi.org/10.1007/s13369-020-04384-y
Annalakshmi M, Roomi SMM, Naveedh AS (2019) A hybrid technique for gender classification with SLBP and HOG features. Cluster Comput 22:11–20. https://doi.org/10.1007/s10586-017-1585-x
Barz B, Denzler J (2019) Hierarchy-based image embeddings for semantic image retrieval. Proc - 2019 IEEE winter Conf Appl Comput vision, WACV. 2019:638–647. https://doi.org/10.1109/WACV.2019.00073
Bel KNS, Shatheesh Sam I (2020) Encrypted image retrieval method using SIFT and ORB in cloud. 2020 7th Int Conf smart Struct Syst ICSSS 2020 4–8. https://doi.org/10.1109/ICSSS49621.2020.9202374
Chen L, Qiu L, Li KC, Shi W, Zhang N (2017) DMRS: an efficient dynamic multi-keyword ranked search over encrypted cloud data. Soft Comput 21:4829–4841. https://doi.org/10.1007/s00500-017-2684-6
Content Based Image Retrieval / Image Database Search Engine (SIMPLIcity, WIPE, Virtual Microscope). http://wang.ist.psu.edu/docs/related/. Accessed 22 Nov 2019
Cui H, Zhu L, Li J, Yang Y, Nie L (2020) Scalable deep hashing for large-scale social image retrieval. IEEE Trans Image Process 29:1271–1284. https://doi.org/10.1109/TIP.2019.2940693
Curtmola R, Garay J, Kamara S, Ostrovsky R (2011) Searchable symmetric encryption: improved definitions and efficient constructions. J Comput Secur 19:895–934. https://doi.org/10.3233/JCS-2011-0426
Galshetwar GM, Waghmare LM, Gonde AB, Murala S (2019) Local energy oriented pattern for image indexing and retrieval. J Vis Commun Image Represent 64:102615. https://doi.org/10.1016/j.jvcir.2019.102615
Garg M, Dhiman G (2020) A novel content-based image retrieval approach for classification using GLCM features and texture fused LBP variants. Neural Comput Appl:0123456789. https://doi.org/10.1007/s00521-020-05017-z
Hu S, Xu C, Guan W, Tang Y, Liu Y (2014) Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis. Biomed Mater Eng 24:129–143. https://doi.org/10.3233/BME-130793
Huang F, Jin C, Zhang Y, Weng K, Zhang T, Fan W (2018) Sketch-based image retrieval with deep visual semantic descriptor. Pattern Recogn 76:537–548. https://doi.org/10.1016/j.patcog.2017.11.032
Huang J, Kumar SR, Mitra M et al (1997) Image indexing using color correlograms. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit:762–768. https://doi.org/10.1109/cvpr.1997.609412
K Nalini Sujantha Bel ISS (2009) IS e C ure. 1–17. https://doi.org/10.22042/isecure.2020.209056.497
Khawandi S, Abdallah F, Ismail A (2019) A survey on image indexing and retrieval based on content based image. Proc Int Conf Mach Learn Big Data, Cloud Parallel Comput Trends, Prespectives Prospect Com 2019:222–225. https://doi.org/10.1109/COMITCon.2019.8862184
Krishnaraj N, Elhoseny M, Lydia EL, et al (2020) An efficient radix trie-based semantic visual indexing model for large-scale image retrieval in cloud environment. Softw - Pract Exp 1–14. https://doi.org/10.1002/spe.2834
Latif A, Rasheed A, Sajid U, et al (2019) Content-based image retrieval and feature extraction: A comprehensive review Math Probl Eng 2019: https://doi.org/10.1155/2019/9658350
Li JS, Liu IH, Tsai CJ, Su ZY, Li CF, Liu CG (2020) Secure content-based image retrieval in the cloud with key confidentiality. IEEE Access 8:114940–114952. https://doi.org/10.1109/ACCESS.2020.3003928
Li Y, Ma J, Miao Y, Wang Y, Liu X, Choo KKR (2020) Similarity search for encrypted images in secure cloud computing. IEEE Trans Cloud Comput 7161:1–1. https://doi.org/10.1109/tcc.2020.2989923
Liang H, Zhang X, Cheng H (2018) Wei Q (2018) secure and efficient image retrieval over encrypted cloud data. Secur Commun Networks 2018:1–14. https://doi.org/10.1155/2018/7915393
Liang H, Zhang X, Cheng H (2019) Huffman-code based retrieval for encrypted JPEG images. J Vis Commun Image Represent 61:149–156. https://doi.org/10.1016/j.jvcir.2019.03.021
Liu D, Shen J, Xia Z, Sun X (2017) A content-based image retrieval scheme using an encrypted difference histogram in cloud computing. Inf 8:1–13. https://doi.org/10.3390/info8030096
Liu G, Bao H, Han B (2018) A stacked autoencoder-based deep neural network for achieving gearbox fault diagnosis. Math Probl Eng 2018:1–10. https://doi.org/10.1155/2018/5105709
Liu J, Chung FL, Wang S (2018) Black hole entropic fuzzy clustering. IEEE Trans Syst Man, Cybern Syst 48:1622–1636. https://doi.org/10.1109/TSMC.2017.2682883
Mahmoudi SA, Belarbi MA, Dadi EW, Mahmoudi S, Benjelloun M (2019) Cloud-based image retrieval using GPU platforms. Computers 8:1–12. https://doi.org/10.3390/computers8020048
Mathan Kumar B, PushpaLakshmi R (2018) Multiple kernel scale invariant feature transform and cross indexing for image search and retrieval. Imaging Sci J 66:84–97. https://doi.org/10.1080/13682199.2017.1378285
Nalini Sujantha Bel K, Shatheesh Sam I (2021) Black hole entropic fuzzy clustering-based image indexing and Tversky index-feature matching for image retrieval in cloud computing environment. Inf Sci (Ny). https://doi.org/10.1016/j.ins.2021.01.043
Pahariya G, Ravindran Balaraman DS (2018) Dynamic Class Learning Approach for Smart CBIR. 841:481–493. https://doi.org/10.1007/978-981-13-0020-2
Pang S, Orgun MA, Yu Z (2018) A novel biomedical image indexing and retrieval system via deep preference learning. Comput Methods Prog Biomed 158:53–69. https://doi.org/10.1016/j.cmpb.2018.02.003
Pankaja VSK (2018) Leaf recognition and classification using Chebyshev moments. In: Smart Intelligent Computing and Applications. Springer Singapore, pp. 667–678
Qin J, Li H, Xiang X, Tan Y, Pan W, Ma W, Xiong NN (2019) An encrypted image retrieval method based on Harris corner optimization and LSH in cloud computing. IEEE Access 7:24626–24633. https://doi.org/10.1109/ACCESS.2019.2894673
Sergyán S (2008) Color histogram features based image classification in content-based image retrieval systems. SAMI 2008 6th Int Symp Appl Mach Intell informatics - proc 221–224. https://doi.org/10.1109/SAMI.2008.4469170
Singh S, Batra S (2020) An efficient bi-layer content based image retrieval system. Multimed Tools Appl 79:17731–17759. https://doi.org/10.1007/s11042-019-08401-7
Singh VP, Srivastava R (2015) Design & performance analysis of content based image retrieval system based on image classification usingvarious feature sets. 2015 1st Int Conf Futur trends Comput anal Knowl Manag ABLAZE 664–670. https://doi.org/10.1109/ABLAZE.2015.7154946
Sundararajan SK, Sankaragomathi B, Priya DS (2019) Deep Belief CNN Feature Representation Based Content Based Image Retrieval for Medical Images. J Med Syst:43. https://doi.org/10.1007/s10916-019-1305-6
Visual Geometry Group - University of Oxford. http://www.robots.ox.ac.uk/~vgg/data/flowers/102/index.html. Accessed 22 Nov 2019
Wang JZ, Li J, Wiederhold G (2001) SIMPLIcity : semantics-sensitive integrated matching for picture LIbraries. IEEE Trans Pattern Anal Mach Intell 23:947–963
Wang X, Zhang C, Wu Y, Shu Y (2017) A manifold ranking based method using hybrid features for crime scene shoeprint retrieval. Multimed Tools Appl 76:21629–21649. https://doi.org/10.1007/s11042-016-4029-3
Xia Z, Xiong NN, Vasilakos AV, Sun X (2017) EPCBIR: an efficient and privacy-preserving content-based image retrieval scheme in cloud computing. Inf Sci (Ny) 387:195–204. https://doi.org/10.1016/j.ins.2016.12.030
Xia Z, Lu L, Qiu T et al (2019) A privacy-preserving image retrieval based on ac-coefficients and color histograms in cloud environment. Comput Mater Contin 58:27–43. https://doi.org/10.32604/cmc.2019.02688
Xu Y, Zhao X, Gong J (2019) A large-scale secure image retrieval method in cloud environment. IEEE Access 7:160082–160090. https://doi.org/10.1109/ACCESS.2019.2951175
Zaidi SAJ, Buriro A, Riaz M et al (2019) Implementation and comparison of text-based image retrieval schemes. Int J Adv Comput Sci Appl 10:611–618. https://doi.org/10.14569/IJACSA.2019.0100177
Zhang G, Ma ZM (2007) Texture feature extraction and description using Gabor wavelet in content-based medical image retrieval. Proc 2007 Int Conf wavelet anal pattern recognition, ICWAPR ‘07 1:169–173. https://doi.org/10.1109/ICWAPR.2007.4420657
Zneit RA, Alqadi Z, Zalata MA (2017) A methodology to create a fingerprint for RGB color image. Int J Comput Sci Mob Comput 6:205–212
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Bel, K.N.S., Sam, I.S. Incremental indexing with binary feature based Tversky index using black hole entropic fuzzy clustering in cloud computing. Multimed Tools Appl 81, 18457–18481 (2022). https://doi.org/10.1007/s11042-022-12699-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-022-12699-1