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Behrouz Bolourian Haghighi
 
Ph.D. Candidate in Artificial Intelligence and Robotics
Senior Researcher 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

 

 
   
 
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ORCID: Orcid.org/0000-0002-2388-5556ORCID iD icon
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Behrouz Bolourian Haghighi

 
Latest publication
 

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, Available online 14 October 2017, ISSN 1047-3203,

https://www.sciencedirect.com/science/article/pii/S1047320317301876

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  

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JVCI


 

Last Updated on Friday, 23 November 2018 09:30