Browsing by Author "Tsai, Min-Jen"

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A collaborated computing system by web services based P2P architecture
(2006)
Tsai, Min-Jen
;
Wang, Chen-Sheng
;
Yang, Po-Yu
;
Yang, Chien-Yu
;
資訊管理與財務金融系註：原資管所+財金所
The peer-to-peer (P2P) model which shares the content or resources over the network gradually replaces the traditional client/server architecture. A new computing architecture: Computing Power Services (CPS) which utilizes Web Services and Business Process Execution Language (BPEL) to overcome the problems of P2P about flexibility, compatibility and workflow management is proposed in this study. CPS is a lightweight Web Services based P2P power sharing environment, and suitable for enterprise computing works which are able to run in batch format in a trusty network. The architecture relies on BPEL which provides a visualized development environment and workflow control management. In this paper, the collaborated computing system has been applied to analyze the robustness of digital watermark by filter bank selection. As the result of this case, the performance can be improved in the aspect of speedup, efficiency and process time.
A COLOR DIFFERENTIATED FUZZY C-MEANS (CDFCM) BASED IMAGE SEGMENTATION ALGORITHM
(2012)
Tsai, Min-Jen
;
Chang, Hsuan-Shao
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Image segmentation is a very important process in digital image/video processing and computer vision applications. It is often used to partition an image into separated parts for further processes. For some applications (i.e., concept-based image retrieval), a successful segmentation algorithm is necessary to identity the objects effectively. In addition, how to tag the objects after the segmentation associated with keywords is also a challenge for researchers. In this study, we proposed a color differentiated fuzzy c-means (CDFCM) framework for effective image segmentation to achieve segmented objects within image which is useful for further annotation. In our experiments, we compared our approach with other FCM techniques on synthetic image with excellent performance. Furthermore, CDFCM outperforms other approaches by using the Berkeley image segmentation data set with layered annotation, which can be applied for additional operations.
A computing coordination based fuzzy group decision-making (CC-FGDM) for web service oriented architecture
(2008-05-04)
Tsai, Min-Jen
;
Wang, Chen-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
As the demands for faster data processing and enterprise computing are increasing, the traditional client/server architecture has gradually been replaced by Grid computing or the peer-to-peer (P2P) model which can share the content or resources over the network. In this paper, a new computing architecture - computing power services (CPS) - has been applied to utilize web services and business process execution language for overcoming the issues about flexibility, compatibility and workflow management. CPS is a lightweight web services based computing power-sharing architecture, and suitable for enterprise computing tasks which can be executed in the batch processes within a trusty network. However, a real-time load balance and dispatching mechanism is needed for distributed-computing architecture like CPS in order to handle computing resources efficiently and properly. Therefore, a fuzzy group decision-making based adaptive collaboration design for CPS is proposed in this paper to provide the real-time computation coordination and quality of service. In this study, the approach has been applied to analyze the robustness of digital watermark by filter bank selection and the performance can be improved in the aspect of speedup, stability and processing time. This scheme increases the overall computing performance and shows stability for the dynamic environment. (c) 2007 Elsevier Ltd. All rights reserved.
A game-theoretic architecture for visible watermarking system of ACOCOA (adaptive content and contrast aware) technique
(2011)
Tsai, Min-Jen
;
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 watermarking techniques have been developed to protect the intellectual property. A digital watermarking system is basically judged based on two characteristics: security robustness and image quality. In order to obtain a robust visible watermarking in practice, we present a novel watermarking algorithm named adaptive content and contrast aware (ACOCOA), which considers the host image content and watermark texture. In addition, we propose a powerful security architecture against attacks for visible watermarking system which is based on game-theoretic approach that provides an equilibrium condition solution for the decision maker by studying the effects of transmission power on intensity and perceptual efficiency. The experimental results demonstrate that the feasibility of the proposed approach not only provides effectiveness and robustness for the watermarked images, but also allows the watermark encoder to obtain the best adaptive watermarking strategy under attacks.
A game-theoretic framework for the security system of visible watermarking
(2011-05-01)
Tsai, Min-Jen
;
Liu, Jung
;
Wang, Chen-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
Perfect digital watermarking systems are contained two characteristics. One is the robustness that it need be resistant to geometric attacks in addition to common image processing tasks, such as JPEG compression. The other one is to preserve the image quality after embedding. However, the requirement of robustness and quality for watermark are conflicted with each other. How to determine the equilibrium of optimal security strategies between encoder and attacker and the optimal tradeoff between the intensity of embedded watermark and the perceptual translucence for visible watermark is still remained as one of the most challenging research topics in image watermarking. Therefore, in order to achieve the best tradeoff between the embedding energy of watermark, the quality of perceptual watermark translucence and the image fidelity after attacks, we propose a system architecture which is based on the game-theoretic approach that provides an optimum solution for the decision maker by studying the intensity and perceptual efficiency. The game-theoretic approach determines the transmission strategy using utility optimization according to the fluctuation of watermark states. The watermark embedding problem is formulated as a dynamic non-cooperative game with complete information while the optimal strategy is defined by the Nash equilibrium of the game. The experimental results demonstrate the feasibility of the proposed approach which allows the watermark encoder to obtain the best adaptive watermarking strategy in the different texture under attacks. Additionally, we demonstrate that the proposed system could help each user to choose the optimal transmission power to maximize its utility based on other constant parameters and resolve security issue of visual communication. (C) 2010 Elsevier Ltd. All rights reserved.
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.
A visible watermarking algorithm based on the content and contrast aware (COCOA) technique
(2009-07-01)
Tsai, Min-Jen
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
A novel visible watermarking algorithm based on the content and contrast aware (COCOA) technique with the consideration of Human Visual System (HVS) model is presented in this study. In order to determine the optimal watermark locations and strength at the watermark embedding stage, the COCOA visible watermarking utilizes the global and local characteristics of the host and watermark images in the discrete wavelet transform (DWT) domain. To achieve the best tradeoff between the embedding energy of watermark and the perceptual translucence, the utilization of contrast-sensitive function, noise visible function of perceptual model, and the basis function amplitudes of DWT coefficients are fine tuned, for the best quality of perceptual translucence and noise reduction of the COCOA algorithm. The experimental results demonstrate that COCOA technique not only provides high PSNR values for the watermarked images, but also preserves the watermark visibility under various signal processing operations, especially the watermark removal attack. (C) 2009 Elsevier Inc. All rights reserved.
A visible wavelet watermarking technique based on exploiting the contrast sensitivity function and noise reduction of human vision system
(2014-09-01)
Tsai, Min-Jen
;
Liu, Jung
;
Yin, Jin-Sheng
;
Yuadi, Imam
;
資訊管理與財務金融系註：原資管所+財金所
With the widespread use of the Internet and the rapid development of digital technologies, copyright protection of multimedia content has become an important issue. Among the available technologies, digital watermarking techniques are regarded as a solution to the property right protection for multimedia resources. To evaluate the performance of a visible watermarking technique, robustness and perceptual translucence are two essential criteria for the watermark applications. In order to get the best trade-off between the embedding energy of a watermark and perceptual translucence, this study presents a technique named ICOCOA (innovated content and contrast aware) by exploiting the contrast sensitivity function (CSF) and noise reduction of human vision system in the wavelet domain. Another novel idea of this work is to propose the innovated CSF masking (I-CSF) curve which provides better weight perception where a game-theoretic architecture can be leveraged to determine the best I-CSF masking for the watermarked image. The experimental results demonstrate that the proposed approach not only provides a good translucent quality of the watermark but also achieves the robustness against the common image processing operations.
A wavelet-based semi-fragile watermarking with recovery mechanism
(2008)
Tsai, Min-Jen
;
Chien, Chih-Cheng
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
This paper studied the wavelet transformation based watermarking tamper detection and recovery scheme. By the property of discrete wavelet transform, we design the semi-fragile watermark from low-frequency band and embedding the watermark into the high-frequency band by the help of Human Visual System (HVS). The watermarked image still preserves high image quality after the embedding of the semi-fragile watermark and the image authentication system is able to locate precisely any malicious alteration made to the image. Our novel design can restore the altered or destroyed regions from the attacked images and allow the users to know what the original content was in the manipulated areas. We also analyze the robustness for mild modification like JPEG compression and channel additive white Gaussian noise (AWGN) and fragility to malicious attack. In summary, this scheme can resist the mild modifications of digital image and be able to detect the malicious modifications precisely.
A Wavelet-based Watermarking Scheme Using Double Wavelet Tree Energy Modulation
(2008-01-01)
Tsai, Min-Jen
;
Lin, Ching Ting
;
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
Wavelet tree based watermarking algorithms arc generally using the energy difference among grouped wavelet coefficients for invisible watermark embedding and extraction. According to the cryptanalysis of wavelet tree quantization (WTQ) scheme, its robustness has been proven weak and modified wavelet tree quantization (MWTQ) is developed consequently. However, MWTQ needs the wavelet tics group data as the extra information and MWTQ is rot blind for watermark extraction. Therefore, a novel wavelet tire. watermarking using double wavelet tree energy modulation is proposed in this study. This study has performed intensive comparison for the proposed scheme with WTGM and MWTQ under various signal processing attacks. The experiment results demonstrate that the proposed technique yields better performance with higher degree of robustness than WTQ.
A Wavelet-based Watermarking Scheme Using Double Wavelet Tree Energy Modulation
(2008)
Tsai, Min-Jen
;
Lin, Ching-Ting
;
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
Wavelet tree based watermarking algorithms are generally using the energy difference among grouped wavelet coefficients for invisible watermark embedding and extraction. According to the cryptanalysis of wavelet tree quantization (WTQ) scheme, its robustness has been proven weak and modified wavelet tree quantization (MWTQ) is developed consequently. However, MWTQ needs the wavelet tree group data as the extra information and MWTQ is not blind for watermark extraction. Therefore, a novel wavelet tree watermarking using double wavelet tree energy modulation is proposed in this study. This study has performed intensive comparison for the proposed scheme with WTQ, WTGM and MWTQ under various signal processing attacks. The experiment results demonstrate that the proposed technique yields better performance with higher degree of robustness than WTQ.
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.
Adaptive real-time computation coordination for the web services based computing architecture
(2007)
Tsai, Min-Jen
;
Wang, Chen-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
Computation coordination is an important decision making activity in the real-time distributed computing in order to achieve the optimal performance. The Computing Power Sharing (CPS) is a lightweight web services based architecture, and suitable for enterprise computing works which are able to run in batch format within a trusty network. The architecture relies on Business Process Execution Language (BPEL) which provides a visualized development environment and workflow control management. An adaptive real-time coordination module based on fuzzy group decision making policy that implements fuzzy resolution process facilitates the CPS architecture to provide the real-time computation coordination with quality of service. In this paper, the collaborated computing system has been applied to analyze the robustness of digital watermark by filter bank selection. As the result of this study, the performance can be improved in the aspect of speedup, stability and process time.
Authentication and recovery for wavelet-based semifragile watermarking
(2008-06-01)
Tsai, Min-Jen
;
Chien, Chih-Cheng
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
We propose a novel image authentication and recovery scheme based on discrete wavelet transform (DWT). By using the property of a DWT multiresolution structure, we generate a semifragile watermark from low-frequency bands and embed the recovery information into the high-frequency bands based on the human visual system (HVS) approach. The image authentication system is able to locate precisely any malicious alteration made to the image and restore the altered or destroyed regions based on the recovery mechanism. Therefore, the requirements of ownership protection and tampering detection of digital right management (DRM) are met, and the legal usage of digital content is available. In addition, robustness to mild modifications like JPEG compression and channel additive white Gaussian noise (AWGN) is also achieved with high recovery image quality. (C) 2008 Society of Photo-Optical Instrumentation Engineers.
Camera/mobile phone source identification for digital forensics
(2007)
Tsai, Min-Jen
;
Lai, Cheng-Liang
;
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 photographs by using the support vector machine (SVM). Based on the fact that the internal imaging formation algorithms of the cameras are different from one manufacturer to another, our approach first calculates the characteristic values of the images taken by different cameras in conjunction with image processing techniques and data exploration methods. The training and categorization procedures of the image characteristic values are further conducted through SVM to identify the source camera of the images. Based on SVM's ability to distinguish cameras of different brands, this study also examines whether the method can differentiate cameras of the same brand, or even the popular mobile phones with camera. The experiment results demonstrate that our approach can achieve higher identification rate for camera and mobile phone sources than the results from other literatures.
Constrained wavelet tree quantization for image watermarking
(2007)
Tsai, Min-Jen
;
Lin, Chen-Long
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
This paper investigates the operations of the wavelet tree based quantization and proposes a constrained wavelet tree quantization for image watermarking. The wavelet coefficients of the cover image are grouped into super trees for watermark embedding where quantization is performed. The watermark bits are extracted based on a modulus approach and the minimum mean comparison of the super tree coefficients efficiently distinguishes which super tree is quantized. Without the needs of the requantization index at the decoder, the constrained quantization of the super trees reduces the uncertainty of the maximum likelihood detection. Therefore, the robustness of the proposed scheme can be effectively improved. This study has performed intensive comparison for the proposed scheme with the non-constrained tree quantization method under various geometric and nongeometric attacks. The experiment results demonstrate that the proposed technique yields better performance with higher degree of robustness.
Decision-theoretic model to identify printed sources
(2018-10-01)
Tsai, Min-Jen
;
Yuadi, Imam
;
Tao, Yu-Han
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
When trying to identify a printed forged document, examining digital evidence can prove to be a challenge. Over the past several years, digital forensics for printed document source identification has begun to be increasingly important which can be related to the investigation and prosecution of many types of crimes. Unlike invasive forensic approach which requires a fraction of the printed document as the specimen for verification, noninvasive forensic technique uses the optical mechanism to explore the relationship between the scanned images and the source printer. To explore the relationship between source printers and images obtained by the scanner, the proposed decision-theoretical approach utilizes image processing techniques and data exploration methods to calculate many important statistical features, including: Local Binary Pattern (LBP), Gray Level Co-occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT), Spatial filters, the Wiener filter, the Gabor filter, Haralick, and SFTA features. Consequently, the proposed aggregation method intensively applies the extracted features and decision-fusion model of feature selections for classification. In addition, the impact of different paper texture or paper color for printed sources identification is also investigated. In the meantime, the up-to-date techniques based on deep learning system is developed by Convolutional Neural Networks (CNNs) which can learn the features automatically to solve the complex image classification problem. Both systems have been compared and the experimental results indicate that the proposed system achieve the overall best accuracy prediction for image and text input and is superior to the existing approaches. In brief, the proposed decision-theoretical model can be very efficiently implemented for real world digital forensic applications.
Deep learning for printed document source identification
(2019-02-01)
Tsai, Min-Jen
;
Tao, Yu-Han
;
Yuadi, Imam
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Due to the rapid development of the information technology and wide use of the Internet, Information is easily to be obtained in the form of digital format. Digital content can be freely printed into documents since the convenience and accessibility of the printers. On the other hand, printed documents can be illegally manipulated by some criminal issues such as: forged documents, counterfeit currency, copyright infringement, and so on. Therefore, how to develop an efficient and appropriate safety testing tool to identify the source of printed documents is an important task in the meantime. Currently, the forensic system using the statistical methods and support vector machine technology has been able to identify the source printer for the text and the image documents. Such an approach belongs to the category of shallow machine learning with human interaction during the stages of feature extraction, feature selection and data pre-processing. In this paper, 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. Systematic experiments have been performed for both systems. For microscopic documents, feature based SVM system outperforms the deep learning system with limited gap. For scanned documents, both system can achieve equally well with high accuracy. Both systems should be constantly evaluated and compared for the best interest in universal utilization.
Differential energy based watermarking algorithm using wavelet tree group modulation (WTGM) and Human Visual System
(2008-08-01)
Tsai, Min-Jen
;
Shen, Chang-Hsing
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Wavelet tree based watermarking algorithms are using the wavelet coefficient energy difference for copyright protection and ownership verification. WTQ (Wavelet Tree Quantization) algorithm is the representative technique using energy difference for watermarking. According to the cryptanalysis on WTQ, the watermark embedded in the protected image can be removed successfully. In this paper, we present a novel differential energy watermarking algorithm based on the wavelet tree group modulation structure, i.e. WTGM (Wavelet Tree Group Modulation). The wavelet coefficients of host image are divided into disjoint super trees (each super tree containing two sub-super trees). The watermark is embedded in the relatively high-frequency components using the group strategy such that energies of sub-super trees are close. The employment of wavelet tree structure, sum-of-subsets and positive/negative modulation effectively improve the drawbacks of the WTQ scheme for its insecurity. The integration of the HVS (Human Visual System) for WTGM provides a better visual effect of the watermarked image. The experimental results demonstrate the effectiveness of our algorithm in terms of robustness and imperceptibility.