PDF Print E-mail
Behrouz Bolourian Haghighi
Ph.D. Candidate in Artificial Intelligence and Robotics
Research Assistant  at Machine Vision Laboratory
Department of Computer Engineering
Ferdowsi University of Mashhad
Mashhad, Iran

Personal details
First Name: Behrouz
Last Name: Bolourian Haghighi
Birthday: August 1991
Hometown: Mashhad, Iran


Contact details
CV: Download
ORCID: Orcid.org/0000-0002-2388-5556ORCID iD icon
Scholar: Behrouz Bolourian Haghighi
LinkedIn: Behrouz Bolourian Haghighi
ResearchGate: Behrouz Bolourian Haghighi
Github: Behrouz Bolourian Haghighi
E-Mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it
Behrouz Bolourian Haghighi

Latest publications

Bolourian Haghighi, B., Taherinia, A., Mohajerzadeh, A. (2019). ‘TRLG: Fragile blind quad watermarking for image tamper detection and recovery by providing compact digests with quality optimized using LWT and GA', Journal of Information Science


Abstract: In this paper, an efficient fragile blind quad watermarking scheme, named TRLG, is proposed for image tamper detection and recovery based on lifting wavelet transform and genetic algorithm. TRLG generates four compact digests with super quality based on lifting wavelet transform and halftoning technique by distinguishing the types of image blocks. In this way, for each 2 × 2 non-overlapping block, four chances for recovering the destroyed blocks are created. A special parameter estimation technique based on the genetic algorithm is performed to improve and optimize the quality of digests and the watermarked image. Furthermore, the Chebyshev System is used to determine the mapping block for embedding, encrypting, and shuffling the information. To improve the recovery rate, two techniques called Mirror-aside and Partner-block are proposed. Some experiments are conducted to prove the superiority of TRLG in terms of quality of the watermarked and recovered images, tamper localization, and security compared with the state-of-the-art methods. The results indicate that the average values of PSNR and SSIM of the watermarked image are about 46 dB and 1, respectively. Also, the average values of PSNR and SSIM for several recovered images that were destroyed about 90% reached to 24 dB and 0.86, respectively.

Keywords: Data hiding; Watermarking; Tamper detection and recovery; Texture analysis; Genetic algorithm; Lifting wavelet transform; Halftoning technique.  



Behrouz Bolourian Haghighi, Amir Hossein Taherinia, Ahad Harati, TRLH: Fragile and blind dual watermarking for image tamper detection and self-recovery based on lifting wavelet transform and halftoning technique, Journal of Visual Communication and Image Representation, Volume 50, 2018, Pages 49-64, ISSN 1047-3203.


Abstract: This paper proposes a fragile and blind dual watermarking method for tamper detection and self-recovery. This method generates two image digests from the host image, based on the lifting wavelet and the halftoning technique. Therefore, for each 2 × 2 non-overlapping blocks, two chances for recovering tampered blocks is provided. Then, the authentication bit is obtained by using the image digests. Totally, eight bits are embedded in two LSBs for each block of image. To enhance the quality of the digest, a new LSB Rounding technique is proposed. Additionally, to determine the mapping blocks and shuffling LSBs, the Arnold Cat Map is utilized. To improve the recovery rate, a Shift-aside operation is proposed. For preventing copy-move, vector-quantization attacks, and any manipulation in LSBs, the information embedded in each block depends on the key which is assigned to it. Experimental results show the efficiency of TRLH compared to the state of the art methods.

Keywords: Data hiding; Watermarking; Tamper detection and self-recovery; Image authentication; Lifting wavelet transform; Halftoning technique  




Last Updated on Thursday, 10 October 2019 22:00