Tamper detection and recovery for medical images using near-lossless information hiding technique

doi:10.1007/s10278-007-9011-1

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Journal Article > Item 987654321/122981

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/122981

Title:	Tamper detection and recovery for medical images using near-lossless information hiding technique
Authors:	Wu, Jeffery H.K.;Chang, Ruey-Feng;Chen, Chii-Jen;Wang, Ching-Lin;Kuo, Ta-Hsun;Moon, Woo Kyung;Chen, Dar-Ren
Keywords:	Medical image;image processing;image authentication
Date:	2007-03-28
Issue Date:	2023-04-28 16:33:33 (UTC+8)
Publisher:	Springer New York LLC
Abstract:	Digital medical images are very easy to be modified for illegal purposes. For example, microcalcification in mammography is an important diagnostic clue, and it can be wiped off intentionally for insurance purposes or added intentionally into a normal mammography. In this paper, we proposed two methods to tamper detection and recovery for a medical image. A 1024 × 1024 x-ray mammogram was chosen to test the ability of tamper detection and recovery. At first, a medical image is divided into several blocks. For each block, an adaptive robust digital watermarking method combined with the modulo operation is used to hide both the authentication message and the recovery information. In the first method, each block is embedded with the authentication message and the recovery information of other blocks. Because the recovered block is too small and excessively compressed, the concept of region of interest (ROI) is introduced into the second method. If there are no tampered blocks, the original image can be obtained with only the stego image. When the ROI, such as microcalcification in mammography, is tampered with, an approximate image will be obtained from other blocks. From the experimental results, the proposed near-lossless method is proven to effectively detect a tampered medical image and recover the original ROI image. In this study, an adaptive robust digital watermarking method combined with the operation of modulo 256 was chosen to achieve information hiding and image authentication. With the proposal method, any random changes on the stego image will be detected in high probability.
Relation:	Journal of Digital Imaging 21(1), p.59-76
DOI:	10.1007/s10278-007-9011-1
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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