Separation of overlapping text from graphics
The separation of overlapping text from graphics is a challenging problem in document image analysis. This paper proposes a specific method for detecting and extracting characters that are touching graphics. It is based on the observation that the constituent strokes of characters are usually short segments in comparison with those of graphics. It combines line continuation with the feature line width to decompose and reconstruct segments underlying the region of intersection. Experimental results showed that the proposed method improved the percentage of correctly detected text as well as the accuracy of character recognition significantly.

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: 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: 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: The use of bigrams to enhance text categorization
abstract: In this paper, we present an efficient text categorization algorithm that generates bigrams selectively by looking for ones that have an especially good chance of being useful. The algorithm uses the information gain metric, combined with various frequency thresholds. The bigrams, along with unigrams, are then given as features to two different classifiers: Naive Bayes and maximum entropy. The experimental results suggest that the bigrams can substantially raise the quality of feature sets, showing increases in the break-even points and F1 measures. The McNemar test shows that in most categories the increases are very significant. Upon close examination of the algorithm, we concluded that the algorithm is most successful in correctly classifying more positive documents, but may cause more negative documents to be classified incorrectly.

title: An Investigation of Online Group-Buying Institution and Buyer Behavior
abstract: This study draws on interdependency theory to propose and assess the effects of two artifacts - conditional purchase and information cue - on decisional choice in the online group-buying context. Our results suggest that buyers presented with conditional purchase options (i.e., of not honoring the purchase when the expected discount price is not met) are more willing to make a purchase choice (i.e., deviate from an inactive inertia). Counter-intuitively, provision of information cues (i.e., information about procurement actions of the other buyers) appears to induce inaction. However, when a choice has to be made between a riskier and a less risky choice, the presence of information cues leads to a higher propensity for the riskier choice. Implications for theory and practice are further discussed.

title: Key Substitution Attacks on Provably Secure Short Signature Schemes
abstract: Recently, Boneh et al. proposed provably secure short signature schemes in the standard model and in the random oracle model respectively. In this letter, we propose strong-key substitution attacks on these signature schemes. In one of the attacks, we show that an adversary can generate a new public key satisfying all legitimate signatures created by the legitimate signer.

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: Functional Principles of Registry-based Service Discovery
abstract: As service discovery protocols (SDP) are becoming increasingly important for ubiquitous computing, they must behave according to predefined principles. We present the functional principles of service discovery for robust, registry-based service discovery. A methodology to guarantee adherence to these principles is provided and illustrated by formal verification of the principles against FRODO, an SDP built for the home environment. We show that, to make behavioral guarantees, an SDP has to be robust against network disturbances, and cannot rely only on the network layer