A crisscross checking technique for tamper detection in halftone images

Authors:
Jeanne Chen;Tung-Shou Chen;Yu-Mei Pan
Affiliations:
Department of Computer Science Information Management, Hung-Kuang University, Taichung 433, Taiwan, ROC;Department of Information Management, National Taichung Institute of Technology, Taichung 404, Taiwan, ROC;Department of Information Management, National Taichung Institute of Technology, Taichung 404, Taiwan, ROC
Venue:
Journal of Systems and Software
Year:
2005

Citing 6
Cited 1

A method for obtaining digital signatures and public-key cryptosystems

Communications of the ACM
Data hiding by smart pair toggling for halftone images

ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Optimized halftoning using dot diffusion and methods for inverse halftoning

IEEE Transactions on Image Processing
Look-up table (LUT) method for inverse halftoning

IEEE Transactions on Image Processing
Data hiding watermarking for halftone images

IEEE Transactions on Image Processing
Tree-structured method for LUT inverse halftoning and for image halftoning

IEEE Transactions on Image Processing

Watermarking in halftone images with parity-matched error diffusion

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

As the race for digital technological advancements accelerates, foremost is the troubling concern for better protection for digital data. Unequivocally, detecting for tamper in data poses a great challenge to information security and image processing. In this paper, a crisscross checking technique is proposed for tamper detection in halftone images. First, a host image is divided into NxN blocks. The individual blocks will be scrambled with a random number into code-strings which will be concatenated into rows and columns code-streams. Finally, these code-streams will be applied to the MD5 and RSA algorithms to generate encrypted signed messages that will be hidden in the blocks. For the detection process, the row and column blocks will be checked for these signed messages which will be extracted, decrypted and compared to the rows and columns blocks of the image for dissimilar bits as sign of tamper. The tampered row and column blocks will be crisscrossed and the intersecting blocks will be identified as tampered areas.