Abstract
Perceptual image hashing technique uses the appearance of the digital media object as human eye and generates a fixed size hash value. This hash value works as digital signature for the media object and it is robust against various digital manipulation done on the media object. This technique have been constantly in use in various application areas like content-based image retrieval, image authentication, digital watermarking, image copy detection, tamper detection, image indexing, etc., but it is difficult to generate a perfect perceptual image hash function due to the inverse relationship between its main properties i.e. perceptual robustness and discriminative capability. In this paper, a robust and desirable discrimination capable dual perceptual image hash functions are proposed which use fuzzy color histogram for hash generation. The fuzzy engine needs stable color representation to generate a robust fuzzy color histogram feature which is invariant to various content preserving attacks like gaussian low pass filtering, jpeg compression, etc. To satisfy this, \(CIEL^{*}a^{*}b^{*}\) color space forms an good basis as it approximates the human visual system and it is also uniform and device independent color space. The robustness of the fuzzy color histogram is further increased by selecting the most significant bins using an experimentally selected tuning factor and the same is furthermore normalized to make it scale invariant. Our experimentation shows that hash generated with this feature is more stable and able to handle various content preserving attacks and performs better as compared to the latest techniques. Both the proposed systems able to maintain good balance between perceptual robustness with optimal TPR when the FPR \(\simeq \)0 is 0.8115 and 0.8264 and discrimination capability with the optimal FPR when TPR\(\simeq \)1 is 0.0618 and 0.0208 respectively.
Similar content being viewed by others
References
Ahmed F, Mohammed YS, Abbas VU (2010) A secure and robust hash-based scheme for image authentication. Signal Process 90:1456–1470
Arambam N, Singh KM (2016) Perceptual hash function based on scale-invariant feature transform and singular value decomposition. Comput J 59:1275–1281
Burger W, Burge MJ (2009) Principles of digital image processing: core algorithms. Springer-Verlag, London
Choi YS, Park JH (2012) Image hash generation method using hierarchical histogram. Multimed Tools Appl 61:181–194
Fridrich J, Goljan M (2000) Robust hash functions for digital watermarking. In: Proc Int Conf information technology: coding and computing, pp 178–183
Gonzalez RC, Woods RE (2007) Digital image processing, 3rd edn. Prentice-Hall, Englewood Cliffs
Hassan E, Chaudhury S, Gopal M (2012) Feature combination in Kernel space for distance based image hashing. IEEE Trans Multimed 14:1179–1195
Hernandez RAP, Miyatake MN, Kurkoski BM (2011) Robust image hashing using image normalization and SVD decomposition. Int Midwest Sympos Circ Syst, 1–4
https://homepages.cae.wisc.edu/∼ece533/images/. Accessed July 2016
Jie Z (2013) A novel Block-DCT and PCA based image perceptual hashing algorithm. IJCSI Int J Comput Sci 10:399–403
Küçüktunç O, Güdükbay U, Ulusoy ö (2010) Fuzzy color histogram-based video segmentation. Comput Vis Image Underst 114:25–134
Lefèbvre F, Macq B, Legat JD (2002) RASH: radon soft hash algorithm. In: Proc Int conf signal processing conference, European, pp 1–4
Konstantinidis K, Gasteratos A, Andreadis I (2005) Image retrieval based on fuzzy color histogram processing. Optics Commun 248:4–6:375–386
Kucuktunc O., Zamalieva D. (2009) Fuzzy color histogram-based CBIR system. In: Proc Int fuzzy systems, symposium, pp 231–234
mathworld.wolfram.com. http://mathworld.wolfram.com/Line.html. Accessed February 2017
Photo database. http://www.petitcolas.net/watermarking/image_database/. Accessed July 2016
Olmos A, Kingdom FA (2004) A biologically inspired algorithm for the recovery of shading and reflectance images. Perception 33:1463–147
Slaney M, Casey M (2008) Locality-sensitive hashing for finding nearest neighbors. IEEE Signal Process Mag 25:128–131
Tang Z, Wang S, Zhang X, Wei W, Su S (2008) Robust image hashing for tamper detection using non-negative matrix factorization. J Ubiquitous Converg Technol 2:18–26
Tang Z, Zhang X, Dai X, Yang J, Wu T (2013) Robust image hash function using local color features. Int J Electron Common (AEU) 67:717–722
Tang Z, Zhang X, Huang L, Dai Y (2013) Robust image hashing using ring-based entropies. Signal Process 93:2061–2069
Tang ZJ, Zhang XQ, Dai YM, Lan WW (2013) Perceptual image hashing using local entropies and DWT. Imag Sci J 61:2:241–251
Tang Z, Dai Y, Zhang X, Huang L, Yang F (2014) Robust image hashing via colour vector angles and discrete wavelet transform. IET Image Process 8:3:142–149
Tang Z, Yang F, Huang L, Zhang X (2014) Robust image hashing with dominant DCT Co-efficients. Optik-Int J Light Electron Opt 125:5102–5107
Tang Z, Zhang X, Zhang S (2014) Robust perceptual image hashing based on ring partition and NMF. IEEE Trans Knowl Data Eng 26:711–724
Tang Z, Zhang X, Li X, Zhang S (2016) Robust image hashing with ring partition and invariant vector distance. IEEE Trans Inf Forens Secur 11:200–214
USC-SIPI Image Databa. http://sipi.usc.edu/database/. Accessed July 2016
Weng L, Preneel B (2009) Shape-based features for image hashing. Int Conf Multimed Expo, 1074–1077
Xiang S, Kim HJ, Huang J (2007) Histogram-based image hashing scheme robust against geometric deformations. In: Proc Int conf multimedia & security. Dallas, pp 121–128
Yang B, Gu F, Niu X (2006) Block mean value based image perceptual hashing. Int Conf on Int Inf Hiding Multimed, 167–172
Zauner C (2010) Implementation and benchmarking of perceptual image hash functions. Master’s thesis, Upper Austria University of Applied Sciences
Zhao Y, Wang S, Zhang X, Yao H (2013) Robust hashing for image authentication using Zernike moments and local features. IEEE Trans Inf Forens Secur 8:1:55–63
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gharde, N.D., Thounaojam, D.M., Soni, B. et al. Robust perceptual image hashing using fuzzy color histogram. Multimed Tools Appl 77, 30815–30840 (2018). https://doi.org/10.1007/s11042-018-6115-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-018-6115-1