• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.7-13
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• 2018

The methods for detecting copy move frogery (CMF) are divided into two categories, block-based methods and keypoint-based methods. Block-based methods have a high computational cost because a large number of blocks should be examined for CMF detection. In addition, the forgery detection may fail if a tampered region undergoes geometric transformation. On the contrary, keypoint-based methods can overcome the disadvantages of the block-based approach, but it can not detect a tampered region if the CMF forgery occurs in the low entropy region of the image. Therefore, in this paper, we propose a method to detect CMF forgery in all areas of image by combining keypoint-based and block-based methods. The proposed method first performs keypoint-based CMF detection on the entire image. Then, the areas for which the forgery check is not performed are selected and the block-based CMF detection is performed for them. Therefore, the proposed CMF detection method makes it possible to detect CMF forgery occurring in all areas of the image. Experimental results show that the proposed method achieves better forgery detection performance than conventional methods.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.153-162
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• 2020

Digital image forgery detection is one of very important fields in the field of digital forensics. As the forged images change naturally through the advancement of technology, it has made it difficult to detect forged images. In this paper, we use passive forgery detection for copy paste forgery in digital images. In addition, it detects copy-paste forgery using the L₀ Norm-based LE operator, and compares the detection accuracy with the forgery detection using the existing L₂, L₁ Norm-based LE operator. In comparison of detection rates, the proposed lower triangular(Ayalneh and Choi) window was more robust to BAG mismatch detection than the conventional window filter. In addition, in the case of using the lower triangular window, the performance of image forgery detection was measured increasingly higher as the L₂, L₁ and L₀ Norm LE operator was performed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1259-1267
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• 2016

With the growing use of fingerprint authentication systems in recent years, the fake fingerprint detection is becoming more and more important. This paper mainly proposes a method for fake fingerprint detection based on CNN, it will visualize the distinctive part of detected fingerprint which provides a deeper insight in CNN model. After the preprocessing part using fingerprint segmentation, the pretrained CNN model is used for detecting the liveness detection. Not only a liveness detection but also feature analysis about the live fingerprint and fake fingerprint are provided after classifying which materials are used for making the fake fingerprint. Our system is evaluated on three databases in LivDet2013, which compromise almost 6500 live fingerprint images and 6000 fake fingerprint images in total. The proposed method achieves 3.1% ACE value about the liveness detection and achieves 79.58% accuracy on LiveDet2013.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.293-294
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• 2017

본 논문에서는 CNN 기반 서명인식에서 시간정보를 이용하여 위조서명을 보다 정확하게 판별하는 방법을 제안한다. 시간정보를 이용하는 첫 번째 방법은 서명하는 전체 시간을 동일한 개수의 등 간격으로 나누어 각각의 이미지를 얻고 이를 합성하여 이용하는 방법이다. 두 번째 방법은 동일한 개수의 등 간격으로 나누어진 각각의 이미지를 CNN-LSTM 으로 판별하는 방법이다. 동일한 개수의 등 간격으로 나누어진 이미지들에는 서명의 속도에 따른 모양의 차이가 발생하기 때문에 비록 최종 서명의 모양이 원본과 매우 유사하다고 하더라도 속도가 다른 경우 위조임을 판별할 수 있다. 두 명의 서명에 대하여 실험을 한 결과 최종 서명이 매우 유사하더라도 속도가 다른 경우 위조로 판별할 수 있음을 보였다. 다만 이미지 합성 과정에 만들어진 새로운 정보로 인하여 진짜 서명을 가짜로 판별할 수 있는 가능성도 늘어날 수 있음을 확인하였다.

• Journal of Digital Convergence
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• v.14 no.6
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• pp.133-142
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• 2016

The purpose of this study is to test the effects of brand image and product similarity with the original on the attitude toward the counterfeit of prestige brand. Especially this study is focused on the moderating effect of perceived bland globalness (PBG) and the influence of the original attitude on the counterfeit one. The results of this study are as follows 1) brand image has a positive impact on the counterfeit attitude as well as the original one. And symbolic image is more positive than functional image on the both of them. 2)The moderating effect of PBG appeared between brand image and attitude. Namely, there is no statistical difference according to PBG in the effect of brand image on the original attitude. But the effect of brand image on the counterfeit attitude is higher in case of high PBG. 3) Product similarity of the counterfeit with the original has a positive impact on only the counterfeit attitude. And the similarity of perceived quality is more positive than appearance similarity on the counterfeit attitude. 4) The original attitude has a positive impact on the counterfeit one.

• Journal of IKEEE
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• v.22 no.2
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• pp.227-232
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• 2018

Nowadays, image manipulation is enormously popular and easier than ever with tons of convenient images editing tools. After several simple operations, users can get visually attractive images which easily trick viewers. In this paper, we propose a fast algorithm which can detect the image splicing using the Markov features. The proposed algorithm reduces the computational complexity by removing unnecessary Markov features which are not used in the image splicing detection process. The performance of the proposed algorithm is evaluated using a famous image splicing dataset which is publicly available. The experimental results show that the proposed technique outperforms the state-of-the-art splicing detection methods.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.4
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• pp.1-12
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• 2018

Currently, a large amount of printed matter associated with code authentication method are diffused widely, however, they have been reproduced with great precision and distributed successively in illegal ways. In this paper, we propose an efficient code authentication method which classifies authentic or counterfeit with smart-phone, effectively. The proposed method stores original image code in the server side and then extracts multiple comparison measures describing the original image. Based on these multiple measures, a code authentication algorithm is designed in such a way that counterfeit printed images may be effectively classified and then the recognition rate may be highly improved. Through real experiments, it is shown that the proposed method can improve the recognition rate greatly and lower the mis-recognition rate, compared with single measure method.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.279-286
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• 2004

본 논문에서는 출입국자 관리의 효율성과 체계적인 출입국 관리를 위하여 위조 여권을 판별할 수 있는 지능형 여권 얼굴 인증 시스템을 제안한다. 제안하는 지능형 여권 얼굴 인증 시스템은 여권 이미지에서 여권 코드 문자열을 인식하여 여권 사용자의 사진 및 관련 정보를 여권 데이터베이스에서 추출한다. 추출된 출입국자의 사진 및 얼굴과 여권에 부착된 사진 및 얼굴과의 유사도 측정을 통하여 여권 사진의 위조 여부을 판단한다. 이때, 이미지의 유사도 측정을 위해서 다양한 실험을 통한 결과를 종합 분석해 본 결과 사진 영역의 인증에는 Luminance, Edge, RGB 특징이, 얼굴 영역의 인증을 위해서는 Hue, YIQ-I, YCbCr-Cb 특징이 효과적인 것으로 나타났으며 사진 영역의 유사도와 얼굴영역의 유사도가 모두 0.8이상인 경우 정상적인 여권으로 판정하고 그렇지 않은 경우 위조가 되었을 가능성이 있는 여권으로 판정하는 방법을 사용하여 FAR 3.1%, FRR 2.7%의 우수한 결과를 나타내었다.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.389-395
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• 2015

Digital image provides many conveniences at the internet environment recently. A great number of applications, like Digital Library, Stock Image, Personal Image and Important Information, require the use of digital image. However it has fatal defect which is easy to be modified because digital image is only electronic file. Numerous digital image forgeries have become a serious problem due to the sophistication and accessibility of image editing software. Copy-Move forgery is the simplest type of forgery that involves copying portion of an image and paste it on different location within the image. There are many approaches to detect Copy-Move forgery, but all of them have their own limitations. In this paper, visual and invisible feature based forgery detection techniques are tested and analyzed. The analysis shows that pros and cons of these two techniques compensate each other. Therefore, a hybrid of visual based and invisible feature based forgery detection that combine the merits of both techniques is proposed. The experimental results show that the proposed algorithm has enhanced performance compared to individual techniques. Moreover, it provides more information about the forgery, like identifying copy and duplicate regions.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.5
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• pp.163-172
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• 2014

The Scale Invariant Feature Transform (SIFT) has been widely used in a lot of applications for image feature matching. Such a transform allows us to strong matching ability, stability in rotation, and scaling with the variety of different scales. Recently, it has been made one of the most successful algorithms in the research areas of copy-move forgery detections. Though this transform is capable of identifying copy-move forgery, it does not widely address the possibility that counter-forensics operations may be designed and used to hide the evidence of image tampering. In this paper, we propose a targeted counter-forensics method for impeding SIFT-based copy-move forgery detection by applying a semantically admissible distortion in the processing tool. The proposed method allows the attacker to delude a similarity matching process and conceal the traces left by a modification of SIFT keypoints, while maintaining a high fidelity between the processed images and original ones under the semantic constraints. The efficiency of the proposed method is supported by several experiments on the test images with various parameter settings.