A nearest-neighbor chain based approach to skew estimation in document images
A nearest-neighbor chain (NNC) based approach is proposed in this paper to develop a skew estimation method with a high accuracy and with language-independent capability. Size restriction is introduced to the detection of nearest-neighbors (NN). Then NNCs are extracted from the adjacent NN pairs, in which the slopes of the NNCs with a largest possible number of components are computed to give the skew angle of document image. Experimental results on various types of documents containing different linguistic scripts and diverse layouts show that the proposed approach has achieved an improved accuracy for estimating document image skew angle and has an advantage of being language independent.

title: Improving Pronoun Resolution Using Statistics-Based Semantic Compatibility Information
abstract: In this paper we focus on how to improve pronoun resolution using the statistics-based semantic compatibility information. We investigate two unexplored issues that influence the effectiveness of such information: statistics source and learning framework. Specifically, we for the first time propose to utilize the web and the twin-candidate model, in addition to the previous combination of the corpus and the single-candidate model, to compute and apply the semantic information. Our study shows that the semantic compatibility obtained from the web can be effectively incorporated in the twin-candidate learning model and significantly improve the resolution of neutral pronouns.

title: Chart analysis and recognition in document images
abstract: Hidden Markov models are a probabilistic modeling tool for time series data. It has been successfully applied to many areas, such as speech recognition, hand-written character recognition, etc. In this paper, we present a novel statistical approach using ergodic hidden Markov models to recognize scientific charts. We also present a newly developed feature extraction method for chart images. Unlike traditional primitive-based diagram recognition method, our approach need not recognize the graphic primitives in charts thus bypassing the recognition error problem caused by the inaccurate primitive extraction that is also a major obstacle to the construction of a general chart recognition system.

title: Document Flattening through Grid Modeling and Regularization
abstract: For document images captured by a digital camera, perspective and geometric distortions make it hard to recognize the document content properly. In this paper, we propose an integrated document restoration technique, which is capable of removing perspective and geometric distortions, and producing a flattened and fronto-parallel text image that is friendly to the generic OCR systems. The proposed document restoration is accomplished through grid modeling, which divides camera images into multiple quadrilateral grids using vertical text directions and the x lines and base lines. The global distortions are then removed through grid regularization that transforms the quadrilateral grids together with the pixel contents to the regular square grids. Experimental results show the proposed method is fast and easy for implementation

title: Motion deblurring for optical character recognition
abstract: This paper investigates the problem of blurring caused by motion during image capture of text documents. Motion blurring prevents proper optical character recognition of the document text contents. One area of such applications is to deblur name card images obtained from handheld cameras. In this paper, a complete motion deblurring procedure for document images has been proposed. The method handles both uniform linear motion blur and uniform acceleration motion blur. Experiments on synthetic and real-life blurred images prove the feasibility and reliability of this algorithm provided that the motion is not too irregular. The restoration procedure consumes only small amount of computation time.

title: Correcting document image warping based on regression of curved text lines
abstract: Image warping is a common problem when one scans or photocopies a document page from a thick bound volume, resulting in shading and curved text lines in the spine area of the bound volume. This will not only impair readability, but will also reduce the OCR accuracy. Further to our earlier attempt to correct such images, this paper proposes a simpler connected component analysis and regression technique. Compared to our earlier method, the present system is computationally less expensive and is resolution independent too. The implementation of the new system and improvement of OCR accuracy are presented in this paper.

title: Comparison-Shopping Websites: An Empirical Investigation on the Influence of Decision Aids and Information Load on Consumer Decision-Making Behavior
abstract: Rapid advances in Internet commerce technology have brought about the emergence of comparison-shopping Websites, which act as agents to consolidate vast amounts of product information. Researchers have traditionally focused on incorporating the latest database interrogation technology and investigating the economic implications of the existence of comparison-shopping Websites. Little attention has been paid to understanding whether the decision aids provided are capable of assisting a consumer in managing a large quantity of information or, more importantly, are compatible with the decision-making behavior of the consumer. This study surveys several successful comparison-shopping Websites, enumerates two comercially successful forms of decision aids (i.e., screening and sorting), and examines their effects on decision effectiveness under different information loads. Based on a 3×2×2 factorial controlled experiment, we had three major findings. First, more sophisticated screening aids that assist a consumer in filtering a large quantity of information do not necessarily improve decision effectiveness. Surprisingly, our results even suggest that in some circumstances the opposite could be true. Second, the results indicate that the effectiveness of decision aids, to a large extent, depends on the information load. Third, decision makers are adaptive. One may supplement the absence of more sophisticated screening aids with the sorting aid.

title: A Distributed Throttling Approach for Handling High Bandwidth Aggregates
abstract: Public-access networks need to handle persistent congestion and overload caused by high bandwidth aggregates that may occur during times of flooding-based DDoS attacks or flash crowds. The often unpredictable nature of these two activities can severely degrade server performance. Legitimate user requests also suffer considerably when traffic from many different sources aggregates inside the network and causes congestion. This paper studies a family of algorithms that "proactively" protect a server from overload by installing rate throttles in a set of upstream routers. Based on an optimal control setting, we propose algorithms that achieve throttling in a distributed and fair manner by taking important performance metrics into consideration, such as minimizing overall load variations. Using ns-2 simulations, we show that our proposed algorithms 1) are highly adaptive by avoiding unnecessary parameter configuration, 2) provide max-min fairness for any number of throttling routers, 3) respond very quickly to network changes, 4) are extremely robust against extrinsic factors beyond the system control, and 5) are stable under given delay bounds.

title: E-governance: towards a strategic convergence of stakeholder interests
abstract: E-governments have become an integral part of our lives and the study of this phenomenon has revealed valuable insights from a governance perspective. Based on an in-depth case study, this paper addresses the strategic management of stakeholders within the e-governmental environment. In particular, the research looks at how advances in information technology have altered the power structures of governance systems and reshaped its fundamental principles .The study concludes that the strategic conversion of interests between the organizations and its stakeholders is an important determining factor for the success of any e-initiative. This requires both a rethinking of fundamental functions and a transformation of organizational business mentalities in order to be flexible and adaptable to ever-changing expectations of a dynamic system.

title: Signature Schemes Based on 3rd Order Shift Registers
abstract: In this paper, we propose two digital signature schemes based on a third order linear feedback shift register. One of them is a normal signature scheme for signing document and the other is with encryption for intended reciever. These two signature schemes are different from most of the signature schemes which are based on discrete logarithm problem, elliptic curves discrete logarithm problem, RSA or quadratic residues. The efficient computational algorithm for computing kth term of a sequence is also presented. The advantage of these two schemes is that the computation is carried out in the ground field and not in an extension field. We also show that the security of these two signature schemes is equivalent to that of Schnorr signature scheme and Signed-ElGamal encryption scheme respectively.

title: Key Substitution Attacks on Some Provably Secure Signature Schemes