• Journal of Information Processing Systems
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• 제14권1호
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• pp.6-31
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• 2018

With the rapid development of the science and technology, it has been becoming more and more convenient to obtain abundant information via the diverse multimedia medium. However, the contents of the multimedia are easily altered with different editing software, and the authenticity and the integrity of multimedia content are under threat. Forensics technology is developed to solve this problem. We focus on reviewing the blind image forensics technologies for copy-move forgery in this survey. Copy-move forgery is one of the most common manners to manipulate images that usually obscure the objects by flat regions or append the objects within the same image. In this paper, two classical models of copy-move forgery are reviewed, and two frameworks of copy-move forgery detection (CMFD) methods are summarized. Then, massive CMFD methods are mainly divided into two types to retrospect the development process of CMFD technologies, including block-based and keypoint-based. Besides, the performance evaluation criterions and the datasets created for evaluating the performance of CMFD methods are also collected in this review. At last, future research directions and conclusions are given to provide beneficial advice for researchers in this field.

• 대한임베디드공학회논문지
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• 제17권6호
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• pp.309-317
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• 2022

In this paper, we propose a machine learning-based copy-move forgery detection network with dual branches. Because the rotation or scaling operation is frequently involved in copy-move forger, the conventional convolutional neural network is not effectively applied in detecting copy-move tampering. Therefore, we divide the input into rotation-invariant and scaling-invariant features based on the wavelet coefficients. Each of the features is input to different branches having the same structure, and is fused in the combination module. Each branch comprises feature extraction, correlation, and mask decoder modules. In the proposed network, VGG16 is used for the feature extraction module. To check similarity of features generated by the feature extraction module, the conventional correlation module used. Finally, the mask decoder model is applied to develop a pixel-level localization map. We perform experiments on test dataset and compare the proposed method with state-of-the-art tampering localization methods. The results demonstrate that the proposed scheme outperforms the existing approaches.

• 한국멀티미디어학회논문지
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• 제21권3호
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• pp.342-347
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• 2018

We proposed a fast detection of copy-move image forgery using four step search algorithm in the spatial domain. In the four-step search algorithm, the search area is 21 (-10 ~ +10), and the number of pixels to be scanned is 33. Our algorithm reduced computational complexity more than conventional copy move image forgery methods. The proposed method reduced 92.34 % of computational complexity compare to exhaustive search algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4467-4486
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• 2018

Trying to deal with the problem of low robustness of Copy-Move Forgery Detection (CMFD) under various transformation and degradation attacks, a novel CMFD method is proposed in this paper. The main advantages of proposed work include: (1) Discrete Analytical Fourier-Mellin Transform (DAFMT) and Locality Sensitive Hashing (LSH) are combined to extract the block features and detect the potential copy-move pairs; (2) The Euclidian distance is incorporated in the pixel variance to filter out the false potential copy-move pairs in the post-verification step. In addition to extracting the effective features of an image block, the DAMFT has the properties of rotation and scale invariance. Unlike the traditional lexicographic sorting method, LSH is robust to the degradations of Gaussian noise and JEPG compression. Because most of the false copy-move pairs locate closely to each other in the spatial domain or are in the homogeneous regions, the Euclidian distance and pixel variance are employed in the post-verification step. After evaluating the proposed method by the precision-recall-$F_1$ model quantitatively based on the Image Manipulation Dataset (IMD) and Copy-Move Hard Dataset (CMHD), our method outperforms Emam et al.'s and Li et al.'s works in the recall and $F_1$ aspects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4567-4587
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• 2017

With the growth of the Internet and the extensive applications of image editing software, it has become easier to manipulate digital images without leaving obvious traces. Copy-move is one of the most common techniques for image forgery. Image blind forensics is an effective technique for detecting tampered images. This paper proposes an improved copy-move forgery detection method based on the discrete cosine transform (DCT). The quantized DCT coefficients, which are feature representations of image blocks, are truncated using a truncation factor to reduce the feature dimensions. A method for judging whether two image blocks are similar is proposed to improve the accuracy of similarity judgments. The main transfer vectors whose frequencies exceed a threshold are found to locate the copied and pasted regions in forged images. Several experiments are conducted to test the practicability of the proposed algorithm using images from copy-move databases and to evaluate its robustness against post-processing methods such as additive white Gaussian noise (AWGN), Gaussian blurring, and JPEG compression. The results of experiments show that the proposed scheme effectively detects both copied region and pasted region of forged images and that it is robust to the post-processing methods mentioned above.

• 한국멀티미디어학회논문지
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• 제22권5호
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• pp.527-534
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• 2019

Recently, Photo editing softwares such as digital cameras, Paintshop Pro, and Photoshop digital can create counterfeit images easily. Various techniques for detection of tamper images or forgery images have been proposed in the literature. A form of digital forgery is copy-move image forgery. Copy-move is one of the forgeries and is used wherever you need to cover a part of the image to add or remove information. Copy-move image forgery refers to copying a specific area of an image itself and pasting it into another area of the same image. The purpose of copy-move image forgery detection is to detect the same or very similar region image within the original image. In this paper, we proposed fast detection of forgery image using four step search based on discrete cosine transform and a four step search algorithm using discrete cosine transform (FSSDCT). The computational complexity of our algorithm reduced 34.23 % than conventional DCT three step search algorithm (DCTTSS).

• 한국멀티미디어학회논문지
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• 제16권4호
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• pp.411-417
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• 2013

In this paper, we proposed a fast detection method of copy-move forgery image based on low frequency coefficients of the DCT coefficients. We proposed a new matching criterion of copy-moved forgery image detection (MCD) using discrete cosine transform. For each $8{\times}8$ pixel block, the DCT transform is calculated. Our algorithm uses low frequency four (DC, 3 AC coefficient) and six coefficients (DC, 5 AC coefficients) of DCT per $8{\times}8$ pixel block. Our algorithm worked block matching for DCT coefficients of the $8{\times}8$ pixel block is slid by one pixel along the image from the upper left corner to the lower right corner. Our algorithm can reduce computational complexity more than conventional copy moved forgery detection algorithms.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권5호
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• pp.163-172
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• 2014

Scale Invariant Feature Transform (SIFT)은 높은 매칭 능력과 회전이나 스케일 조정 시 안정성으로 인해 이미지 특징 매칭을 위해 많은 응용에서 사용되어지고 있으며, 이러한 특성으로 인해 카피-무브 위조 검출을 위한 핵심 알고리즘으로 각광받고 있다. 하지만 SIFT 변환은 이미지 조작의 증거를 감출 수 있는 안티포렌식의 가능성이 높음에도 불구하고 이에 대한 연구는 거의 없으므로, 본 논문에서는 의미론적으로 허용될 수 있는 왜곡을 적용하여 SIFT 기반 카피-무브 위조 검출을 방해하기 위한 타켓 카운터-포렌식 기법을 제안한다. 제안 기법은 공격자가 유사성 매칭 절차를 속일 수 있는 동시에 SIFT 키포인트의 변형을 통한 추적을 방해하여 이미지 조작의 증거를 숨길 수 있는 방안을 제공한다. 또한 제안 기법은 의미론적 제약 하에서 가공된 이미지와 원본 이미지 간의 높은 충실도를 유지하는 특성을 가진다. 한편, 다양한 조건의 테스트 이미지에 대한 실험을 통해 제안 기법의 효율성을 확인하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.695-697
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• 2006

Elshayal $Smart{\copyright}$ software is an almost First Arabian GIS $software{\copyright}$ which completely developed by Arabian developers team and independent of any commercial software package. The software current Features are View and Edit shape files, build new layers, add existing layers, remove layers, swap layers, save layers, set layer data sources, layer properties, zoom in & zoom out, pan, identify, selecting features, invert selection, show data table, data query builder, location query builder, build network, find shortest path, print map, save map image, copy map image to clipboard, save project map, edit move vertex, edit move features, snap vertexes, set vertex XY, move settings, converting coordinate system, applying VB script, copy selected features to another layer, move selected features to another layer, delete selected features, edit data table, modify table structure, edit map features, drawing new features, GPS tracking, 3D view, etc... The software expected Features are: Viewing raster image and image geo-referencing, read other map formats such as DXF Format and Tiger Line Format.

• 인터넷정보학회논문지
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• 제19권4호
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• pp.7-13
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• 2018

Copy move frogery(CMF) 위조를 검출하는 기술은 블록(block) 기반 방식과 특징점(keypoint) 기반 방식으로 구분 된다. 블록 기반 방법은 위조 검출 과정에서 조사해야 하는 블록의 수가 많기 때문에 높은 계산 비용이 발생한다. 또한 위조되는 영역이 기하학적 변환을 거친 경우 위조 검출에 실패하는 단점이 있다. 반대로 특징점 기반 접근법은 블록 기반 방식의 단점을 극복 할 순 있지만 CMF 위조가 이미지의 낮은 엔트로피 영역에서 발생하는 경우 검출 할 수 없다는 단점이 존재한다. 따라서 본 논문에서는 특징점 기반 방식과 블록 기반 방식을 융합하여 이미지의 모든 영역에서 CMF 위조를 검출하는 방법을 제안한다. 제안하는 방법은 우선 전체 이미지를 대상으로 특징점 기반 위조 검출을 수행한다. 그 후 위조 검사가 이루어지지 않은 영역을 선별하여 블록 기반 위조 검사를 다시 수행한다. 따라서 제안하는 위조 검출 기술은 이미지의 모든 영역에서 발생하는 CMF 위조를 검출하는 것을 가능하게 해준다. 실험을 통해 제안하는 방법이 기존은 방법보다 우수한 위조 검출 성능을 보이는 것을 확인하였다.