Edge-preserving prefiltering for document image binarization
We propose a novel coplanar filter, which exploits the coplanarity of the gray-level distribution of neighboring pixels, to pre-filter document images. Experiments show that the proposed filter exhibits the following desired properties for document image binarization: (1) impulsive noise removal; (2) piecewise smoothing; (3) sharp edge preservation.

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: 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: 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: 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: 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: An Empirical Investigation of the Auction Buyer's Choice to Buy Out or Bid: Cry of Regret or Laugh of Satisfaction?
abstract: Online auction buyers often face the predicament of choosing between the buyout strategy and the bidding strategy to acquire an auctioned product. A buyer who chooses to buy out will obtain the item immediately at the posted price while the one who chooses to bid will have to monitor the bidding process in the hope of acquiring the product at a price lower than the posted one. Despite the wealth of auction literature, relatively few studies empirically assess the buyout option. This study seeks to bridge the gap by investigating how the buyout option (permanent or temporary) and price parameters (starting price and buyout price) affect the formation of two emotions, namely anticipated satisfaction of choice and anticipated regret of outcome, which in turn affect the buying strategy (i.e., buy out or bid). We employ laboratory experiments in our study and our results indicate two interesting findings. First, when the permanent buyout option is available, a buyer is more likely to exhibit loss aversion characteristics and prefer to adopt the buyout strategy. Second, when the temporary buyout option is present, the thought that one could avoid premature ending of auction by exercising the bidding option at the start decreases one’s preference for adopting the buyout strategy. Implications of these results for further research and practice are discussed.

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: A new electronic cash model
abstract: Credit card is currently the most popular electronic payment method on the Internet, but it is not an ideal method from the security and privacy point of view. Electronic cash solves many inherent problems of credit card, such as anonymity and off-line payment, and is widely accepted as an ideal electronic payment method. However, there are issues that are yet to be satisfactorily solved, such as fair traceability and double-spending prevention of off-line schemes. In this paper, we present a customer generated electronic cash model that offers unique trade-off between credit card and traditional off-line electronic cash systems. This model provides anonymity for customers and is technically more secure than credit card systems. It eliminates the withdrawal phase of electronic cash systems, thus it is more convenient for customers to use. In addition, fair traceability is provided in case crimes take place.

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: User Response to Free Trial Restrictions: A Coping Perspective
abstract: Software vendors often provide software for free download but with restrictions (e.g., time and/or functionality restrictions). The question that arises is to what extent the restrictions should be set to induce users to procure the full version. This study seeks to answer this question by looking from two perspectives: expectation-disconfirmation and coping behavior. Building on these perspectives, we present a research model of user's coping reactions toward software restrictions. We seek to understand user reactions (i.e., derivation of coping strategy) when their expectation toward trial restrictions is negatively disconfirmed. It is further posited that situational control could moderate the relationship between expectation disconfirmation and coping responses. We believe this research will contribute to enrich the current IS field and benefit market practitioners.