The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Neha Verma - One of the best experts on this subject based on the ideXlab platform.
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On the spectroscopic examination of printed documents by using a field emission scanning electron microscope with energy-dispersive X-ray spectroscopy (FE-SEM-EDS) and chemometric methods: application in forensic science
Analytical and Bioanalytical Chemistry, 2019Co-Authors: Neha Verma, Raj Kumar, Vishal Sharma, R. Sharma, M. C. Joshi, G. R. Umapathy, Sunil Ohja, Sundeep ChopraAbstract:The detection of computer-generated document forgeries has always been a challenging task for forensic document examiners (FDE). With the aim to support the examination processes, Schottky field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FE-SEM-EDS) is explored as a recent tool to analyze black toners obtained from Laser Printers and photocopier machines. Forty samples each from the Laser Printer and photocopier machines are procured and studied for morphological features, elemental profile, and multivariate analysis. The acquired SEM images and spectra are evaluated to discriminate and classify the toners having a different source of origin. Multivariate analysis is applied to develop a model of classification to successfully classify the printed documents on the basis of the similarities and differences in their composition. Hierarchical cluster analysis (HCA) discriminates the printouts in the forms of groups based on their chemical composition. The Laser Printer and the photocopier printed documents are grouped into 11 and eight clusters, respectively, based on their elemental composition. Cross-validation is further conducted to assess the capabilities of developed principal component analysis (PCA) and linear discriminant analysis (LDA) models for the examination of printouts from unknown origin. Graphical abstract
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analysis of Laser Printer and photocopier toners by spectral properties and chemometrics
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2018Co-Authors: Neha Verma, Raj Kumar, Vishal SharmaAbstract:Abstract The use of Printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from Laser Printers and photocopiers were examined using diffuse reflectance UV–Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for Laser Printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV–Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications.
Jung-ho Choi - One of the best experts on this subject based on the ideXlab platform.
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Color Laser Printer forensic based on noisy feature and support vector machine classifier
Multimedia Tools and Applications, 2013Co-Authors: Jung-ho ChoiAbstract:Digital forensics in the ubiquitous era can enhance and protect the reliability of multimedia content where this content is accessed, manipulated, and distributed using high quality computer devices. Color Laser Printer forensics is a kind of digital forensics which identifies the printing source of color printed materials such as fine arts, money, and document and helps to catch a criminal. This paper present a new color Laser Printer forensic algorithm based on noisy texture analysis and support vector machine classifier that can detect which color Laser Printer was used to print the unknown images. Since each Printer vender uses their own printing process, printed documents from different venders have a little invisible difference looks like noise. In our identification scheme, the invisible noises are estimated with the wiener-filter and the 2D Discrete Wavelet Transform (DWT) filter. Then, a gray level co-occurrence matrix (GLCM) is calculated to analyze the texture of the noise. From the GLCM, 384 statistical features are extracted and applied to train and test the support vector machine classifier for identifying the color Laser Printers. In the experiment, a total of 4,800 images from 8 color Laser Printer models were used, where half of the image is for training and the other half is for classification. Results prove that the presented algorithm performs well by achieving 99.3%, 97.4% and 88.7% accuracy for the brand, toner and model identification respectively.
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MM&Sec - Color Laser Printer forensics with noise texture analysis
Proceedings of the 12th ACM workshop on Multimedia and security - MM&Sec '10, 2010Co-Authors: Jung-ho ChoiAbstract:Color Laser Printers are nowadays abused to print or forge official documents and bills. Identifying the printing source used to print documents will be a step for digital media forensics. This paper presents a color Laser Printer identification method to detect what kind of color Laser Printers is used to print the unknown images. Since each Printer vender uses their own printing process, printed documents from different venders have a little invisible difference looks like noise. In our identification scheme, the invisible noises are estimated with the wiener-filter and then a gray level co-occurrence matrix (GLCM) is calculated to analyze the texture of the noise. From the GLCM, 60 statistical features are extracted and applied to train and test the support vector machine classifier for identifying the color Laser Printers. In the experiment, we use total 2,597 images from 7 color Laser Printers. The results prove that the presented identification method performs well analyzing the noise texture of color printed images.
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color Laser Printer identification through discrete wavelet transform and gray level co occurrence matrix
The Kips Transactions:partb, 2010Co-Authors: Jiyeoun Baek, Jung-ho Choi, Seunggyu Kong, Yeonmo YangAbstract:ABSTRACT High-quality and low-price digital printing devices are nowadays abused to print or forge official documents and bills. Identifying color Laser Printers will be a step for media forensics. This paper presents a new method to identify color Laser Printers with printed color images. Since different Printer companies use different manufactural systems, printed documents from different Printers have little difference in visual. Analyzing this artifact, we can identify the color Laser Printers. First, high-frequency components of images are extracted from original images with discrete wavelet transform. After calculating the gray-level co-occurrence matrix of the components, we extract some statistical features. Then, these features are applied to train and classify the support vector machine for identifying the color Laser Printer. In the experiment, total 2,597 images of 7 Printers (HP, Canon, Xerox DCC400, Xerox DCC450, Xerox DCC5560, Xerox DCC6540, Konica), are tested to classify the color Laser Printer. The results prove that the presented identification method performs well with 96.9% accuracy.Keywords:Digital Forensics, Discrete Wavelet Transform, Gray Level Co-occurrence Matrix, Support Vector Machine Classifier
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Identifying Color Laser Printer Using Noisy Feature and Support Vector Machine
2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, 2010Co-Authors: Jung-ho ChoiAbstract:Color Laser Printers are nowadays abused to forge official documents and bills. Identifying the source used to print documents will be a step for digital media forensics. Each Printer vender applies its specific manufacturing and printing process and that makes printed documents from different venders to have a little invisible difference looks like noise. In this paper, we propose a color Laser Printer identification method which detects the vendor or model of color Laser Printers used to print the unknown images. The invisible noises specific to each Printer are estimated with Wiener-filter and then a gray level co-occurrence matrix (GLCM) is calculated to analyze the noise texture. From the GLCM, 60 statistical features are extracted and applied to train and test the support vector machine classifier for identifying the color Laser Printers. Experimental results on total 2,597 images from 7 color Laser Printers prove that the presented method identifies the color Laser Printers well.
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ICIP - Color Laser Printer identification by analyzing statistical features on discrete wavelet transform
2009 16th IEEE International Conference on Image Processing (ICIP), 2009Co-Authors: Jung-ho Choi, Dong-hyuck Im, Jun-taek OhAbstract:Color Laser Printers are nowadays abused to print or forge official documents and bills. Identifying color Laser Printers will be a step for media forensics. This paper presents a new method to identify color Laser Printers with printed color images. First, 39 noise features of color printed images are extracted from the statistical analysis of the HH sub-band on discrete wavelet transform. Then, these features are applied to train and classify the support vector machine for identifying the color Laser Printer. In the experiment, 9 models of 4 brands, Xerox, Konica, HP, Canon, are tested to classify the brand of color Laser Printer, the color toner, and the model of color Laser Printer. The results prove that the presented identification method performs well using the noise features of color printed images.
Vishal Sharma - One of the best experts on this subject based on the ideXlab platform.
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On the spectroscopic examination of printed documents by using a field emission scanning electron microscope with energy-dispersive X-ray spectroscopy (FE-SEM-EDS) and chemometric methods: application in forensic science
Analytical and Bioanalytical Chemistry, 2019Co-Authors: Neha Verma, Raj Kumar, Vishal Sharma, R. Sharma, M. C. Joshi, G. R. Umapathy, Sunil Ohja, Sundeep ChopraAbstract:The detection of computer-generated document forgeries has always been a challenging task for forensic document examiners (FDE). With the aim to support the examination processes, Schottky field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FE-SEM-EDS) is explored as a recent tool to analyze black toners obtained from Laser Printers and photocopier machines. Forty samples each from the Laser Printer and photocopier machines are procured and studied for morphological features, elemental profile, and multivariate analysis. The acquired SEM images and spectra are evaluated to discriminate and classify the toners having a different source of origin. Multivariate analysis is applied to develop a model of classification to successfully classify the printed documents on the basis of the similarities and differences in their composition. Hierarchical cluster analysis (HCA) discriminates the printouts in the forms of groups based on their chemical composition. The Laser Printer and the photocopier printed documents are grouped into 11 and eight clusters, respectively, based on their elemental composition. Cross-validation is further conducted to assess the capabilities of developed principal component analysis (PCA) and linear discriminant analysis (LDA) models for the examination of printouts from unknown origin. Graphical abstract
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analysis of Laser Printer and photocopier toners by spectral properties and chemometrics
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2018Co-Authors: Neha Verma, Raj Kumar, Vishal SharmaAbstract:Abstract The use of Printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from Laser Printers and photocopiers were examined using diffuse reflectance UV–Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for Laser Printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV–Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications.
Ching-hua Chuang - One of the best experts on this subject based on the ideXlab platform.
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Source color Laser Printer identification using discrete wavelet transform and feature selection algorithms
2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011Co-Authors: Min-jen Tsai, Chen-sheng Wang, Ching-hua ChuangAbstract:It has lately become an important research area of digital forensics to identify the characteristics and the originality of the digital devices. This paper presents a novel method to identify source color Laser Printer by using discrete wavelet transform and feature selection algorithms. To explore the relationship between color Laser Printers and color images obtained by scanning printed documents, the proposed approach utilizes image processing techniques and data exploration methods to calculate the features by applying statistical analysis on discrete wavelet transform of scanned images. A model of support vector machines sequentially will be created and trained by using these features to identify the source brand and model of color Laser Printer. In this study, 10 models of color Laser Printers and color toner from 6 different brands are used for the experiments. The experimental results reach up to 92.4% identification rate which is significantly superior to the existing known method by 5.5%. The testing performance justifies the proposed identification method is very useful for source color Laser Printer identification.
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ISCAS - Source color Laser Printer identification using discrete wavelet transform and feature selection algorithms
2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011Co-Authors: Min-jen Tsai, Chen-sheng Wang, Ching-hua ChuangAbstract:It has lately become an important research area of digital forensics to identify the characteristics and the originality of the digital devices. This paper presents a novel method to identify source color Laser Printer by using discrete wavelet transform and feature selection algorithms. To explore the relationship between color Laser Printers and color images obtained by scanning printed documents, the proposed approach utilizes image processing techniques and data exploration methods to calculate the features by applying statistical analysis on discrete wavelet transform of scanned images. A model of support vector machines sequentially will be created and trained by using these features to identify the source brand and model of color Laser Printer. In this study, 10 models of color Laser Printers and color toner from 6 different brands are used for the experiments. The experimental results reach up to 92.4% identification rate which is significantly superior to the existing known method by 5.5%. The testing performance justifies the proposed identification method is very useful for source color Laser Printer identification.
Antonio J Ricco - One of the best experts on this subject based on the ideXlab platform.
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optically addressable single use microfluidic valves by Laser Printer lithography
Lab on a Chip, 2010Co-Authors: Jose L Garciacordero, Dirk Kurzbuch, Fernando Benitolopez, Dermot Diamond, Antonio J RiccoAbstract:We report the design, fabrication, and characterization of practical microfluidic valves fabricated using Laser Printer lithography. These optofluidic valves are opened by directing optical energy from a solid-state Laser, with similar power characteristics to those used in CD/DVD drives, to a spot of printed toner where localized heating melts an orifice in the polymer layer in as little as 500 ms, connecting previously isolated fluidic components or compartments. Valve functionality, response time, and Laser input energy dependence of orifice size are reported for cyclo-olefin polymer (COP) and polyethylene terephthalate (PET) films. Implementation of these optofluidic valves is demonstrated on pressure-driven and centrifugal microfluidic platforms. In addition, these “one-shot” valves comprise a continuous polymer film that hermetically isolates on-chip fluid volumes within fluidic devices using low-vapor-permeability materials; we confirmed this for a period of one month. The fabrication and integration of optofluidic valves are compatible with a range of polymer microfabrication technologies and should facilitate the development of fully integrated, reconfigurable, and automated lab-on-a-chip systems, particularly when reagents must be stored on chip for extended periods, e.g. for medical diagnostic devices, lab-on-a-chip synthetic systems, or hazardous biochemical analysis platforms.
