Efficient detection of copy-move forgery using polar complex exponential transform and gradient direction pattern

Babu, Sarath; Rao, Ch. Srinivasa

doi:10.1007/s11042-022-12311-6

Cited by 46 publications

(3 citation statements)

References 31 publications

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“…This method is essentially adding new content to the document. The second method is called the copy-move forgery method [2,36], where an adversary copies some existing textual information (e.g., the letter "A") from a document and pastes it somewhere else in the same document.…”

Section: Existing Research and Technologiesmentioning

confidence: 99%

Design of an academic document forgery detection system

Boonkrong

2024

Int. j. inf. tecnol.

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Advances in digital technology and communication are reducing the popularity of physical or paper-based documents, particularly in the official academic field. Many academic institutions have shifted from paper-based academic documents to electronic formats. However, with the availability of document-editing and photo-editing software, an adversary can illegally modify original academic documents to suit their needs. Therefore, it is essential that receivers of these digital academic documents must verify the authenticity and detect the forgery of the documents. In this study, a cryptographic hash function, which is concerned with data integrity, is used to detect modifications of digital academic documents. Experiments were conducted to evaluate the correctness and speed of academic document verification. The proposed system was compared with other conventional methods such as digital signature-based, convolutional neural network, and blockchain-based methods. Our study shows that the proposed system can efficiently detect forged digital academic documents with 100% accuracy and a verification speed of 0.352 ms, which is considerably faster than the current digital signature-based, convolutional neural network and blockchain-based technologies. The proposed cryptographic hash function-based method provides another way to help detect forged academic documents.

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Section: Existing Research and Technologiesmentioning

confidence: 99%

Design of an academic document forgery detection system

Boonkrong

2024

Int. j. inf. tecnol.

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“…To detect CMF, Babu and Rao [5] developed a method employing polar complex exponential transform features. The technique is based on a statistical characteristic for overlapping blocks.…”

Section: Rel Ated Workmentioning

confidence: 99%

Automated identification of copy‐move forgery using Hessian and patch feature extraction techniques

Aydın

2023

Journal of Forensic Sciences

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Copy‐move forgeries are a conceptual sort of image retouching that involves duplicating a portion of an image and moving it to a different position within the original image, whether by modifying the duplicated part or just moving it altogether. To identify cloned portions that have been reproduced into the same digitized image, the suggested hybrid features in this article combine using the Hessian and Raw patch features on gray‐level images. Using a suggested model that combines patch features built on key points detected by the Hessian detector on gray‐level image, localization of duplicated and pasted portions of the manipulated image were found. After using the combined features in the matching step, the parallelism condition was applied together with the random sample consensus method to eliminate mismatches. Two databases, GRIP and the image manipulation dataset (IMD), were used for the detection and characterization, and the empirical findings show that the approach was successful in achieving an F1 score 100% for the GRIP database. Additionally, with the IMD database, it produced a 92.13% F1 score. The proposed method was also shown to be effective by obtaining high F1 scores in images where noise, JPEG compression, and scaling attacks were applied to make forgery detection difficult.

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“…Ethical considerations will be strictly followed throughout the research process. Participants' names and anonymity will be protected at all times, and they will be asked for informed consent [5]. Triangulation is the process of validating and improving the validity and reliability of study results by using several data sources (such as surveys, observations, interviews, and evaluations).…”

Section: Content Analysismentioning

confidence: 99%

Differential Education as an Approach for Improving Future Specialist’s General Competence

2023

Journal of Informatics Education and Research

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Differential education, as an innovative approach, aims to enhance the general competence of future specialists by recognizing and accommodating individual learning styles, preferences, and abilities. This research explores the principles and implementation of a differential education model in the context of higher education, specifically focusing on its potential to foster a well-rounded skill set among future specialists.This research article investigates differential education as a transformative strategy for enhancing the general competence of prospective specialists in various domains. In recent years, the old "one-size-fits-all" approach to education has been called into question, and there is a growing recognition of the need to adapt educational practices to accommodate students' diverse needs, talents, and learning styles. This research investigates the principles, methodologies, and benefits of differential education, as well as its potential to foster a more inclusive, adaptive, and productive learning environment. By analyzing case studies and research data, this research demonstrates how differential education can prepare future specialists to flourish in their respective fields while cultivating a holistic and well-rounded skill set.

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Efficient detection of copy-move forgery using polar complex exponential transform and gradient direction pattern

Cited by 46 publications

References 31 publications

Design of an academic document forgery detection system

Design of an academic document forgery detection system

Automated identification of copy‐move forgery using Hessian and patch feature extraction techniques

Differential Education as an Approach for Improving Future Specialist’s General Competence

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