Vertical bar detection for gauging text similarity of document images
A new method for gauging text similarity of image-based documents using word shape recognition is proposed in this paper. Image features are directly extracted instead of using OCR (optical character recognition). The proposed method forms so-called vertical bar patterns by detecting local extrema points in word units extracted by segmenting the document images. These vertical bar patterns form the feature vector of a document. The pair-wise similarity of document images is measured by calculating the scalar product of two document feature vectors. The proposed method is robust to changing fonts and styles, and is less affected by degradation of document qualities. To test the validity of the method, four corpora of document images were used and the ability of the method to retrieve relevant documents is reported.

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: 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: 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: Low-power group key agreement for heterogeneous wireless networks
abstract: Heterogeneous wireless networks are gaining popularity as users can be connected to these networks without any cables and even when they are mobile. The high power nodes in heterogeneous wireless networks do not have energy constraints but the user nodes, which can be large in numbers, are usually low power energy constrained devices. Therefore, the GKA protocol used to secure group communications in these networks has to take into consideration both the low power nature of the user nodes and the network size. In this paper, we present an energy efficient and scalable GKA protocol, which uses our proposed Contributory Ring-Centralized (ContRi-Central) group model. Besides providing complexity analysis, we also show the computational and communication energy consumption costs analysis of all nodes running our proposed scheme and four other efficient GKA protocols. Both the complexity analysis and energy consumption costs analysis indicate that our proposed scheme is more efficient and suitable for heterogeneous wireless networks.

title: Chosen Ciphertext Security from Identity-Based Encryption Without Strong Condition
abstract: Recently, Canetti et al [11] gave a generic construction (called CHK construction) of public key encryption (PKE) from a selective identity-based encryption scheme combined with a strong one-time signature scheme. Later, few schemes were proposed to improve the efficiency of CHK construction [11], for example, Boneh-Katz scheme  replaced a strong one-time signature with a message authentication code and Boyen-Mei-Waters scheme  was constructed directly from Waters' IBE scheme. But, both constructions have either trade-off the publicly verifiable property or security against adaptive chosen-ciphertext attack. We ask a question whether it is possible to construct an efficient and publicly verifiable PKE scheme from a selective IBE scheme with a weak one-time signature scheme. In this paper, we provide an affirmative answer and construct a public key encryption scheme which preserves the publicly verifiable property and is secure against adaptive chosen-ciphertext attack. The construction of the proposed scheme is based on Boneh-Boyen identity-based encryption (IBE) scheme  and a weak one-time signature scheme (using Waters' signature scheme ) built within Boneh-Boyen IBE scheme. In this construction, one-time signature scheme is not required to be strongly existential unforgeable as Waters' signature scheme is not a strongly existential unforgeability. We also show that the proposed scheme is ”almost” as efficient as the original Boneh-Boyen IBE scheme.

title: Motivating open source software developers: influence of transformational and transactional leaderships
abstract: Open Source Software (OSS) is developed by geographically distributed unpaid programmers. The success of such a seemingly chaotic OSS project will largely depend on how the project leader organizes and motivates the developers to contribute. Grounded on leadership and motivation theories, we proposed and tested a research model that seeks to explain the behavioral effects of a leader on the developers' motivation to contribute. Survey data collected from 118 OSS developers on Sourceforge.net was used to test the research model. The results indicate that leaders' transformational leadership is positively related to developers' intrinsic motivation and leaders' active management by exception, a form of transactional leadership, is positively related to developers' extrinsic motivation.

title: Energy-efficient ID-based group key agreement protocols for wireless networks
abstract: One useful application of wireless networks is for secure group communication, which can be achieved by running a group key agreement (GKA) protocol. One well-known method of providing authentication in GKA protocols is through the use of digital signatures. Traditional certificate-based signature schemes require users to receive and verify digital certificates before verifying the signatures but this process is not required in ID-based signature schemes. In this paper, we present an energy-efficient ID-based authenticated GKA protocol and four energy-efficient ID-based authenticated dynamic protocols, namely join, leave, merge and partition protocol, to handle dynamic group membership events, which are frequent in wireless networks. We provide complexity and energy cost analysis of our protocols and show that our protocols are more energy-efficient and suitable for wireless networks.

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.