Relevant bibliographies by topics / Copy move detection

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Copy move detection'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Copy move detection"

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Alam, Md Iftekhar Hossian Md Tasnim, and Jyotirmoy Ghose. "Image Forgery Detection Using Copy-Move Technique." International Journal of Research Publication and Reviews 4, no. 3 (2023): 1103–7. http://dx.doi.org/10.55248/gengpi.2023.32077.

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Kuznetsov, A. V., and V. V. Myasnikov. "COPY-MOVE IMAGE FORENSICS DETECTION." Computer Optics 37, no. 2 (2013): 244–53. http://dx.doi.org/10.18287/0134-2452-2013-37-2-244-253.

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Prasad Patnayakuni, Siva. "Copy Move Forgery Detection Using an Effective CNN Model." International Journal of Science and Research (IJSR) 11, no. 7 (2022): 758–64. http://dx.doi.org/10.21275/sr22710130316.

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Kaur, Harpreet, Jyoti Saxena, and Sukhjinder Singh. "Key-Point Based Copy-Move Forgery Detection and Their Hybrid Methods: A Review." Journal of Advance Research in Electrical & Electronics Engineering (ISSN: 2208-2395) 2, no. 6 (2015): 06–12. http://dx.doi.org/10.53555/nneee.v2i6.189.

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Copy-move image forgery is one of the tampering techniques that need to be tackled with. Many copy-move forgery detection techniques such as exhaustive search, block and key-point matching based methods have been proposed for the detection of copy-move image forgery. Although key-point based methods were found better than block based methods in terms of computationalefficiency, space complexity and robustness against rotation and scaling. However, key-point based methods also possess a number of limitations. So, researchers have proposed many integrated methods to cope up with the limitations
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Imannisa Rahma, Firstyani, and Ema Utami. "Gaussian Pyramid Decomposition in Copy-Move Image Forgery Detection with SIFT and Zernike Moment Algorithms." Telematika 15, no. 1 (2022): 1–13. http://dx.doi.org/10.35671/telematika.v15i1.1322.

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One of the easiest manipulation methods is a copy-move forgery, which adds or hides objects in the images with copies of certain parts at the same pictures. The combination of SIFT and Zernike Moments is one of many methods that helping to detect textured and smooth regions. However, this combination is slowest than SIFT individually. On the other hand, Gaussian Pyramid Decomposition helps to reduce computation time. Because of this finding, we examine the impact of Gaussian Pyramid Decomposition in copy-move detection with SIFT and Zernike Moments combinations. We conducted detection test in
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Anjali, Diwan, Sharma Rajat, K. Roy Anil, and K. Mitra Suman. "Digital Image Tamperin Gdetection using sift Key-Point." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 1484–89. https://doi.org/10.35940/ijeat.B3761.029320.

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Copy-move imitation is a widespread and generally utilized operation to corrupt digital image. It is considered as the most effective research areas in the domain of blind digital image forensics area. Key point based totally identification techniques have been regarded to be very environment-friendly in exposing copy-move proof because of their steadiness against a number of attacks, as like large-scale geometric movements. Conversely, these techniques don’t have the capabilities to cope with the instances if copy-move forgeries only engage in minor or clean areas, the place the quantit
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Wang, Yitian, and Sei-ichiro Kamata. "Copy Move Image Forgery Detection Based on Polar Fourier Representation." International Journal of Machine Learning and Computing 8, no. 2 (2018): 158–63. http://dx.doi.org/10.18178/ijmlc.2018.8.2.680.

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Prakash, Choudhary Shyam, and Sushila Maheshkar. "Copy-Move Forgery Detection Using DyWT." International Journal of Multimedia Data Engineering and Management 8, no. 2 (2017): 1–9. http://dx.doi.org/10.4018/ijmdem.2017040101.

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In this paper, we proposed a passive method for copy-move region duplication detection using dyadic wavelet transform (DyWT). DyWT is better than discrete wavelet transform (DWT) for data analysis as it is shift invariant. Initially we decompose the input image into approximation (LL1) and detail (HH1) sub-bands. Then LL1 and HH1 sub-bands are divided into overlapping sub blocks and find the similarity between the blocks. In LL1 sub-band the copied and moved blocks have high similarity rate than the HH1 sub-band, this is just because, there is noise inconsistency in the moved blocks. Then we s
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Qazi, Tanzeela, Mushtaq Ali, Khizar Hayat, and Baptiste Magnier. "Seamless Copy–Move Replication in Digital Images." Journal of Imaging 8, no. 3 (2022): 69. http://dx.doi.org/10.3390/jimaging8030069.

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The importance and relevance of digital-image forensics has attracted researchers to establish different techniques for creating and detecting forgeries. The core category in passive image forgery is copy–move image forgery that affects the originality of image by applying a different transformation. In this paper, a frequency-domain image-manipulation method is presented. The method exploits the localized nature of discrete wavelet transform (DWT) to attain the region of the host image to be manipulated. Both patch and host image are subjected to DWT at the same level l to obtain 3l+1 sub-ban
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Kaur, Sharanjit, and Manpreet Kaur. "Novel Method for Copy-Move Forgery Detection." International Journal of Computer Applications 174, no. 18 (2021): 10–14. http://dx.doi.org/10.5120/ijca2021921064.

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Dissertations / Theses on the topic "Copy move detection"

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Khayeat, Ali. "Copy-move forgery detection in digital images." Thesis, Cardiff University, 2017. http://orca.cf.ac.uk/107043/.

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The ready availability of image-editing software makes it important to ensure the authenticity of images. This thesis concerns the detection and localization of cloning, or Copy-Move Forgery (CMF), which is the most common type of image tampering, in which part(s) of the image are copied and pasted back somewhere else in the same image. Post-processing can be used to produce more realistic doctored images and thus can increase the difficulty of detecting forgery. This thesis presents three novel methods for CMF detection, using feature extraction, surface fitting and segmentation. The Dense Sc
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Bhatnagar, Kunal, and Gustav Ekner. "Copy-move Image Forgery Detection with Convolutional Neural Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302507.

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Copy-move manipulation is a forgery method used on images where a small part is copied to another part. This thesis analyses the detection of copy-move forgeries with the help of Convolutional Neural Networks (CNN). The model used is utilizing an existing custom CNN layer to identify features useful for detecting manipulations. The model is trained and validated on data with different grades of manipulation to determine which combinations give the highest accuracy. The grades are determined by the copy-move size, ranging between 10% and 60% of the image size. The results show that training on
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Li, Yuan Man. "SIFT-based image copy-move forgery detection and its adversarial attacks." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3952093.

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Albrechtsen, Justin Scott. "Are intuitive responses more accurate at detecting deception than deliberate responses?" To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2007. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Koebele, Clemens. "Mode-division-multiplexing as a possibility to cope with the increasing capacity demand in optical transmission systems." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00762642.

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Currently deployed optical transmission systems use coherent detection for data rates of 40 Gb/s and 100 Gb/s. Quadrature phase shift keying (QPSK) modulation using four phase levels in combination with polarization division multiplexing (PDM) allows transmitting four bits per symbol. The use of more complex modulation formats, such as 16 level quadrature amplitude modulation (16QAM) allows increasing the data rate. However, this method reduces dramatically the transmission reach. For example, when passing from 100 Gb/s PDM-QPSK to 200 Gb/s PDM-16QAM, the reach is reduced by a factor of five.
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Chen, Ling-Ying, and 陳怜穎. "Pyramid Structure for Copy-Move Forgery Detection." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/27911697635315331597.

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碩士<br>淡江大學<br>資訊工程學系碩士班<br>103<br>This paper solves the passive copy-move detection efficiently. A copy-move attack is defined as a region of an image being replaced by a copy of other region in the same image. The proposed scheme improves the performance on the assumption of the copy-move area being larger than a predefined block size. Test image is partitioned to non-overlapping segmented block according to previous predefined block size. Each comparison block, which is overlapped extracted from a segmented block, is compared with upper-left comparison block of all segmented block. Experimen
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Yang, Ging-Chu, and 楊青矗. "Copy-Move Forgery Detection in Digital Image." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/7jw5nc.

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碩士<br>佛光大學<br>資訊學系<br>97<br>Digital images are easy to be tempered and edited due to availability of image editing software. Generally, image tampering protection can be divided into two kinds: (1) active protection: The original digital image is embedded with a watermark which can be used to detect tampering. (2) passive protection: it does not need any digital watermark or signature but relies on the image processing technology to detect the forgery. Passive approaches have not yet been thoroughly researched. The most common ways to temper a digital image is copy-paste forgery which is used
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Hao-ChiangHsu and 許豪江. "Detection of Copy-Move Forgery Image Using Gabor Descriptor." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/01528765039792755705.

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碩士<br>國立成功大學<br>工程科學系碩博士班<br>100<br>With the advance of science and technology, images are easily accessible to everybody. It is also easy to be changed about the content. Images are usually as criminal evidences and news report. How to make sure if the content is not changed becomes a very important issue. In this research, the Gabor filter is mainly applied to get the features of the image under inspected. It is easy to get the rotation and/or scaling versions of the Gabor filter. An image is divided into overlapped sub-blocks with different block size. Each sub-block is convoluted with a pr
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D'Amiano, Luca. "A new technique for video copy-move forgery detection." Tesi di dottorato, 2017. http://www.fedoa.unina.it/12254/1/DAmiano_Luca_XXX.pdf.

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This thesis describes an algorithm for detecting copy-move falsifications in digital video. The thesis is composed of 5 chapters. In the first chapter there is an introduction to forgery detection for digital images and videos. Chapters 2, 3 and 4 describe in detail the techniques used for the implementation of the detection algorithm. The experimental results are presented in the fifth and last chapter.
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DEEPAK. "A SUPER-SIFT APPROACH FOR COPY-MOVE FORGERY DETECTION." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15910.

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Today’s technological era is described by the outspread of digital images. They are the most ordinary formation of conveying information whether through newspapers, internet, books, magazine, scientific journals or social media. They are used as a powerful proof against various crimes, frauds and as an evidence in various situations. With the evolution of image processing in past few years and many other image editing software, capturing, creating or altering images according to our perspective has become very simple and available. There are several kinds of image tampering like copy-mov
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Books on the topic "Copy move detection"

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Soni, Badal, and Pradip K. Das. Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9.

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J, Indumathi. State-of-The-Art in Block based Copy Move Forgery Detection: ICCS 2014. Edited by Kokula Krishna Hari K. Association of Scientists, Developers and Faculties, 2014.

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Das, Pradip K., and Badal Soni. Image Copy-Move Forgery Detection: New Tools and Techniques. Springer Singapore Pte. Limited, 2022.

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Image Copy-Move Forgery Detection: New Tools and Techniques. Springer, 2023.

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Wells, Sandra K., and Betty L. Alt. Police Women. Greenwood Publishing Group, Inc., 2005. http://dx.doi.org/10.5040/9798400697692.

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It is often said that a woman must do a job twice as well as a man in order to get half the credit. This is particularly true of women in law enforcement. Women have been involved in various forms of policing for the last 100 years, but it wasn’t until the Equal Employment Act of 1970 that women could move from the job of meter maids to patrol and detective work. Yet less than 1% of all top-level cops are women, and there remain significant obstacles in the career paths of women in the force. This book looks at the history of women police officers and provides first-hand accounts of women at e
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Book chapters on the topic "Copy move detection"

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Soni, Badal, and Pradip K. Das. "Oriented FAST Rotated BRIEF and Trie-Based Efficient Copy-Move Forgery Detection Algorithm." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_8.

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Soni, Badal, and Pradip K. Das. "Summing Up." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_9.

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Soni, Badal, and Pradip K. Das. "Key-Points Based Enhanced CMFD System Using DBSCAN Clustering Algorithm." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_6.

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Soni, Badal, and Pradip K. Das. "Copy-Move Forgery Detection Using Local Binary Pattern Histogram Fourier Features." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_3.

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Soni, Badal, and Pradip K. Das. "Blur Invariant Block-Based CMFD System Using FWHT Features." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_4.

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Soni, Badal, and Pradip K. Das. "Introduction." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_1.

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Soni, Badal, and Pradip K. Das. "Geometric Transformation Invariant Improved Block-Based Copy-Move Forgery Detection." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_5.

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Soni, Badal, and Pradip K. Das. "Background Study and Analysis." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_2.

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Soni, Badal, and Pradip K. Das. "Image Copy-Move Forgery Detection Using Deep Convolutional Neural Networks." In Image Copy-Move Forgery Detection. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9041-9_7.

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Rajput, G. G., and Smruti Dilip Dabhole. "Keypoint-Based Copy-Move Area Detection." In International Conference on Innovative Computing and Communications. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4071-4_40.

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Conference papers on the topic "Copy move detection"

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Srivastava, Mayank, and Kashish Varshney. "A Review of Copy-Move Image Forgery Detection." In 2025 5th International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE, 2025. https://doi.org/10.1109/icpcsn65854.2025.11034804.

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Ibrahim, Zainab Shawkat, and Taha Mohammed Hasan. "Copy-Move Image Forgery Detection using Deep Learning Approaches." In 2024 First International Conference on Software, Systems and Information Technology (SSITCON). IEEE, 2024. https://doi.org/10.1109/ssitcon62437.2024.10796779.

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Goel, Amit, Ashish Kumar Chakraverti, and Keshav Gupta. "A Comprehensive Analysis of Copy-Move Forgery Detection Method." In 2025 4th OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 5.0. IEEE, 2025. https://doi.org/10.1109/otcon65728.2025.11070901.

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Patankar, A. B., A. Sukhpal, S. Shetye, and A. ShroffShroff. "Copy move forgery detection." In International Conference & Workshop on Electronics & Telecommunication Engineering (ICWET 2016). Institution of Engineering and Technology, 2016. http://dx.doi.org/10.1049/cp.2016.1145.

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Jaafar, Roqaya Hamad, Zahraa H. Rasool, and Abbas H. Hassin Alasadi. "New Copy-Move Forgery Detection Algorithm." In 2019 International Russian Automation Conference. IEEE, 2019. http://dx.doi.org/10.1109/rusautocon.2019.8867813.

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Bhavya Bhanu M P and Arun Kumar M N. "Copy-move forgery detection using segmentation." In 2017 11th International Conference on Intelligent Systems and Control (ISCO). IEEE, 2017. http://dx.doi.org/10.1109/isco.2017.7855986.

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Karsh, Ram Kumar, Anurag Das, G. Lavanya Swetha, et al. "Copy-move forgery detection using ASIFT." In 2016 1st India International Conference on Information Processing (IICIP). IEEE, 2016. http://dx.doi.org/10.1109/iicip.2016.7975329.

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Kang, Li, and Xiao-ping Cheng. "Copy-move forgery detection in digital image." In 2010 3rd International Congress on Image and Signal Processing (CISP). IEEE, 2010. http://dx.doi.org/10.1109/cisp.2010.5648249.

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Gurbuz, Emre, Guzin Ulutas, and Mustafa Ulutas. "Rotation invariant copy move forgery detection method." In 2015 9th International Conference on Electrical and Electronics Engineering (ELECO). IEEE, 2015. http://dx.doi.org/10.1109/eleco.2015.7394451.

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Pandey, Ramesh Chand, Sanjay Kumar Singh, and K. K. Shukla. "Passive copy-move forgery detection in videos." In 2014 International Conference on Computer and Communication Technology (ICCCT). IEEE, 2014. http://dx.doi.org/10.1109/iccct.2014.7001509.

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Reports on the topic "Copy move detection"

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CT Lung Densitometry, Consensus QIBA Profile. Chair Charles Hatt and Miranda Kirby. • The Publisher is Radiological Society of North America (RSNA)/Quantitative Imaging Biomarkers Alliance (QIBA), 2020. https://doi.org/10.1148/qiba/20200904.

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The goal of a QIBA Profile is to achieve a repeatable and useful level of performance for measures of lung density from quantitative CT using the RA-950 HU and Perc15 biomarkers of emphysema. Please see Appendix C for more detailed information on the calculation of and rationale for RA-950 HU and Perc15 as the biomarkers of choice. The Claim (Section 2) describes the performance in terms of bias and precision of RA-950 HU and Perc15 for detecting change in lung density. The Activities (Section 3) describe how to generate RA-950 HU and Perc15 for longitudinal studies of the change in lung densi
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