• Journal of Korea Multimedia Society
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• v.15 no.2
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• pp.179-194
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• 2012

Digital image forgery is becoming a topic of great interest with regard to honesty in imaging. We can often see forged digital images in a variety of places, such as the internet, and magazines, and in images used in political ads, etc. These can reduce the reliability and factual basis of the information contained in image. Therefore, objectivity is needed to determine if the image is forged so as to prevent confusion in the viewing public. Most digital forgeries consist of image resizing, rotating including the following interpolations. To find evidence of interpolation in forged images, this paper proposes a new method for detecting digital image forgery using general interpolation factors analyzed through re-interpolation algorithm of the forged images in order to determine the differences in the patterns. Through the re-interpolation algorithm we could detect the forged region and filtering region used image retouching included to interpolation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.662-675
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• 2018

Compression history detection plays an important role in digital multimedia forensics. Most existing works, however, mainly focus on digital image and video. Additionally, the existed audio compression detection algorithms aim to detect the trace of double compression. In real forgery scenario, multiple compression is more likely to happen. In this paper, we proposed a detection algorithm to reveal the compression history for MP3 audio. The statistics of the scale factor and Huffman table index which are the parameters of MP3 codec have been extracted as the detecting features. The experimental results have shown that the proposed method can effectively identify whether the testing audio has been previously treated with single/double/triple compression.

• Annual Conference of KIPS
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• 2010.11a
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• pp.1118-1121
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• 2010

With the advent of cell phone digital cameras, and sophisticated photo editing software, digital images can be easily manipulated and altered. Although good forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. Most digital camera equipped in cell phones employ a single image sensor in conjunction with a color filter array (CFA), and then interpolates the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed when tampering with an image. We quantify the specific correlations introduced by CFA interpolation, and describe how these correlations, or lack thereof, can be automatically detected in any portion of an image. We show the efficacy of this approach in revealing traces of digital tampering in lossless and lossy compressed color images interpolated with several different CFA algorithms in test cell phones.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.39-47
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• 2005

This paper proposes and analyzes the MAC(Message Authentication Code) algorithm that is used for the transition integrity and the entity authentication of message. The MAC algorithm uses the DES algorithm which has 64-bit block and 56-bit key and we compare the security according to 64-bit and 32-bit length of MAC value. Moreover, we use the SEED algorithm which has 128-bit block and 128-bit key and compare the security according to 128-bit and 64-bit length of MAC value. We analyze the security the forgery attack according to length of message and length of MAC value. this paper, a coarse-to-fine optical flow detection method is proposed. Provided that optical flow gives reliable approximation to two-dimensional image motion, it can be used to recover the three-dimensional motion. but usually to get the reliable optical flows are difficult. The proposed algorithm uses Horn's algorithm (or detecting initial optical flow, then Thin Plate Spline is introduced to warp a image frame of the initial optical flow to the next image frame. The optical flow for the warped image frame is again used iteratively until the mean square error between two image sequence frames is lowered. The proposed method is experimented for the real moving Picture image sequence. The proposed algorithm gives dense optical flow vectors.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.160-167
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• 2014

This paper presents a spliced color image detection method using Benford' Law and color difference. For a suspicious image, after color conversion, the discrete wavelet transform and the discrete cosine transform are performed. We extract the difference between the ideal Benford distribution and the empirical Benford distribution of the suspicious image as features. The difference between Benford distributions for each color component were also used as features. Our method shows superior splicing detection performance using only 13 features. After training the extracted feature vector using SVM classifier, we determine whether the presence of the image splicing forgery. Experimental results show that the proposed method outperforms the existing methods with smaller number of features in terms of splicing detection accuracy.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.152-159
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• 2014

In this paper, we introduce a run-length for wavelet coefficients and present a image splicing detection method using the statistical moments for the wavelet run-length. Various pre-processings for the suspicious image are performed to emphasize the discontinuous edges caused by the image splicing. The proposed scheme has the merit that can exploit the various statistical characteristics of the wavelet transform. We extracted up to 72 features, and performed training and testing using SVM(support vector machine). Experimental results showed that the proposed method generates similar detection results compared to the existing methods. In addition, we showed the wavelet domain run-length is useful to detect the spliced image.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.558-568
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• 2021

The digital image to be accepted as legal evidence, it is important to verify the authentication of the digital image. This study proposes a method of authenticating digital images through three steps of comparing the file structure of digital images taken with iPhone, analyzing the encoding information as well as media logs of the iPhone storing the digital images. For the experiment, digital image samples were acquired from nine iPhones through a camera application built into the iPhone. And the characteristics of file structure and media log were compared between digital images generated on the iPhone and digital images edited through a variety of image editing tools. As a result of examining those registered during the digital image creation process, it was confirmed that differences from the original characteristics occurred in file structure and media logs when manipulating digital images on the iPhone, and digital images take with the iPhone. In this way, it shows that it can prove its forensic authentication in iPhone.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.39-45
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• 2017

Conventional Color-Based Face Recognition Methods are Sensitive to Illumination Changes, and there are the Possibilities of Forgery and Falsification so that it is Difficult to Apply to Various Industrial Fields. In This Paper, we propose a Face Recognition Method Based on LBP(Local Binary Pattern) using the Depth Images to Solve This Problem. Face Detection Method Using Depth Information and Feature Extraction and Matching Methods for Face Recognition are implemented, the Simulation Results show the Recognition Performance of the Proposed Method.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.95-99
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• 2011

Digital forensics is the emerging research field for determining digital forgeries. Key issues of the tampered images are to solve the problems for detecting the interpolation factor and the tampered regions. This paper describes a method to detect the interpolation factors and the forged maps using the differential method and fast Fourier transform(FFT) along the horizontal, vertical, and diagonal direction, respectively from digital filtered tampered images. The detection map can be used to find out interpolated regions from the tempered image. Experimental results demonstrate the proposed algorithm proves effective on several filtering images by adobe $Photoshop^{TM}$ and show a ratio of detecting the interpolated regions and factors from digital filtered composite images.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.250-255
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional 5$\times$5 gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether genuine or forged with more than 98% overall accuracy even without any knowledge of vaned freehand forgeries.