Journal ArticleDOI
Digital forensics of printed source identification for Chinese characters
Min-Jen Tsai,Jin-Shen Yin,Imam Yuadi,Jung Liu +3 more
- Vol. 73, Iss: 3, pp 2129-2155
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TLDR
The superior testing performance demonstrates that the proposed identification method is very useful for source laser printer identification and explores the optimum feature subset by using feature selection techniques and use support vector machine (SVM) to identify the source model of the documents.Abstract:Â
Recently, digital forensics, which involves the collection and analysis of the origin digital device, has become an important issue. Digital content can play a crucial role in identifying the source device, such as serve as evidence in court. To achieve this goal, we use different texture feature extraction methods such as graylevel co-occurrence matrix (GLCM) and discrete wavelet transform (DWT), to analyze the Chinese printed source in order to find the impact of different output devices. Furthermore, we also explore the optimum feature subset by using feature selection techniques and use support vector machine (SVM) to identify the source model of the documents. The average experimental results attain a 98.64 % identification rate which is significantly superior to the existing known method of GLCM by 1.27 %. The superior testing performance demonstrates that the proposed identification method is very useful for source laser printer identification.read more
Citations
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Journal ArticleDOI
Laser printer attribution: exploring new features and beyond.
Anselmo Ferreira,Luiz Claudio Navarro,Giuliano Pinheiro,Jefersson A. dos Santos,Anderson Rocha +4 more
TL;DR: Novel techniques for laser printer attribution are proposed that outperform techniques described in the literature and present near-perfect classification accuracy being very promising for deployment in real-world forensic investigations.
Journal ArticleDOI
Data-Driven Feature Characterization Techniques for Laser Printer Attribution
Anselmo Ferreira,Luca Bondi,Luca Baroffio,Paolo Bestagini,Jiwu Huang,Jefersson A. dos Santos,Stefano Tubaro,Anderson Rocha +7 more
TL;DR: This paper explores solutions able to learn discriminant-printing patterns directly from the available data during an investigation, without any further feature engineering, and proposes the first approach based on deep learning to laser printer attribution.
Journal ArticleDOI
Single Classifier-based Passive System for Source Printer Classification using Local Texture Features
Sharad Joshi,Nitin Khanna +1 more
TL;DR: In this paper, the authors proposed a system for classification of source printer from scanned images of printed documents using all the printed letters simultaneously using local texture patterns based features and a single classifier.
Journal ArticleDOI
Deep learning for printed document source identification
TL;DR: A deep learning system to solve the complex image classification problem is developed by Convolutional Neural Networks (CNNs) of deep learning which can learn the features automatically and should be constantly evaluated and compared for the best interest in universal utilization.
Journal ArticleDOI
Decision-theoretic model to identify printed sources
TL;DR: The proposed decision-theoretical model can be very efficiently implemented for real world digital forensic applications and is superior to the existing approaches.
References
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Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI
Textural Features for Image Classification
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Journal ArticleDOI
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
TL;DR: A type of operator for aggregation called an ordered weighted aggregation (OWA) operator is introduced and its performance is found to be between those obtained using the AND operator and the OR operator.