Browsing by Author "Wang, Cheng-Sheng"

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A HYBRID MODEL FOR DIGITAL CAMERA SOURCE IDENTIFICATION
(2009-01-01)
Tsai, Min-Jen
;
Wang, Cheng-Sheng
;
Liu, Jung
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Digital forensics has lately become one of the very important applications to identify the characteristics and the originality of the digital devices. This study has focused on analyzing the relationship between digital cameras and the images. In conjunction with image processing techniques and data exploration methods, it calculates the characteristic values of the images taken by different cameras. Training and categorization are conducted through the support vector machines for identifying the camera source of the images. Based on the fact that the internal imaging algorithms of a camera are different from one manufacturer to another, this method computes the hidden characteristics of the images. The result of experiments shows the proposed approach can obtains 94.95% identification rate when images are taken from 20 different cameras.
A HYBRID MODEL FOR DIGITAL CAMERA SOURCE IDENTIFICATION
(2009-01-01)
Tsai, Min-Jen
;
Wang, Cheng-Sheng
;
Liu, Jung
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Digital forensics has lately become one of the very important applications to identify the characteristics and the originality of the digital devices. This study has focused on analyzing the relationship between digital cameras and the images. In conjunction with image processing techniques and data exploration methods, it calculates the characteristic values of the images taken by different cameras. Training and categorization are conducted through the support vector machines for identifying the camera source of the images. Based on the fact that the internal imaging algorithms of a camera are different from one manufacturer to another, this method computes the hidden characteristics of the images. The result of experiments shows the proposed approach can obtains 94.95% identification rate when images are taken from 20 different cameras.
Adaptive feature selection for digital camera source identification
(2008)
Tsai, Min-Jen
;
Wang, Cheng-Sheng
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Digital forensics which identifies the characteristics and the originality of the digital devices has lately become one of the very important applications. If it wants to serve as the evidence to the court like its traditional counterparts, the digital forensics issues like verifying the authenticity of digital image, detecting the forged regions or identifying digital camera source of an image will need to be addressed. This study has focused on analyzing the relationship between digital cameras and the photographs by using the support vector machine (SVM). In this paper, several feature selection algorithms will be implemented with SVM-based classifier to increase the predicting accuracy rate of identifying digital camera source of an image. The experiment results demonstrate that our adaptive feature selection scheme can achieve higher identification rate for unbiased camera sources than the results without using feature selection approaches.