38916969
A Generic System for Form Dropout
Recent advances in intelligent character recognition are enabling us to address many challenging problems in document image analysis. One of them is intelligent form analysis. This paper describes a generic system for form dropout when the filled-in characters or symbols are either touching or crossing the form frames. We propose a method to separate these characters from form frames whose locations are unknown. Since some of the character strokes are either touching or crossing the form frames, we need to address the following three issues: 1) localization of form frames; 2) separation of characters and form frames; and 3) reconstruction of broken strokes introduced during separation. The form frame is automatically located by finding long straight lines based on the block adjacency graph. Form frame separation and character reconstruction are implemented by means of this graph. The proposed system includes form structure learning and form dropout. First, a form structure-based template is automatically generated from a blank form which includes form frames, preprinted data areas and skew angle. With this form template, our system can then extract both handwritten and machine-typed filled-in data. Experimental results on three different types of forms show the performance of our system. Further, the proposed method is robust to noise and skew that is introduced during scanning.
46138594
Document Representation and Its Application to Page Decomposition
Transforming a paper document to its electronic version in a form suitable for efficient storage, retrieval, and interpretation continues to be a challenging problem. An efficient representation scheme for document images is necessary to solve this problem. Document representation involves techniques of thresholding, skew detection, geometric layout analysis, and logical layout analysis. The derived representation can then be used in document storage and retrieval. Page segmentation is an important stage in representing document images obtained by scanning journal pages. The performance of a document understanding system greatly depends on the correctness of page segmentation and labeling of different regions such as text, tables, images, drawings, and rulers. We use the traditional bottom-up approach based on the connected component extraction to efficiently implement page segmentation and region identification. A new document model which preserves top-down generation information is proposed based on which a document is logically represented for interactive editing, storage, retrieval, transfer, and logical analysis. Our algorithm has a high accuracy and takes approximately 1.4 seconds on a SGI Indy workstation for model creation, including orientation estimation, segmentation, and labeling (text, table, image, drawing, and ruler) for a 2550/spl times/3300 image of a typical journal page scanned at 300 dpi. This method is applicable to documents from various technical journals and can accommodate moderate amounts of skew and noise.
41609314
A robust and fast skew detection algorithm for generic documents
Abstract A robust and fast skew detection algorithm based on hierarchical Hough transform is proposed. It is capable of detecting the skew angle for various document images, including technical articles, postal labels, handwritten text, forms, drawings and bar codes. The algorithm is robust even when black margins introduced by photocopying are present in the image and when the document is scanned at a low resolution of 50 dpi. The algorithm consists of two steps. In the first step we quickly extract the centroids of connected components using a graph data structure. Then, a hierarchical Hough transform (at two different angular resolutions) is applied to the selected centroids. The skew angle corresponds to the location of the highest peak in the Hough space. The performance of the algorithm is shown on a number of document images collected from various application domains. The algorithm is not very sensitive to algorithmic parameters. For an A4 size document image scanned at 50 dpi (typically 413 × 575 pixels), our algorithm is able to detect the skew angle with an accuracy of 0.1° in 0.4s of CPU time on a SunSparc 20 workstation.
34534588
Lane boundary detection using a multiresolution Hough transform
Lane boundary detection is the problem of estimating the geometric structure of the lane boundaries of a road based on the images grabbed by a camera on board a vehicle. We use the Hough transform to detect lane boundaries with a parabolic model under a variety of road pavement types, lane structures and weather conditions. In the three-dimensional Hough space, a parabolic curve is represented as a straight line. To simplify the computation, the parametric space can be divided into (i) a two-dimensional space measured by the parameters which are shared by all the lane edges, and (ii) a one-dimensional space of the parameter which makes a distinction among different edges in an image. A multiresolution strategy is used to improve both the speed and accuracy of the Hough transform. Experimental results show that the proposed method is relatively less prone to the image noise and is computationally tractable.
27633879
A more efficient branch and bound algorithm for feature selection
Abstract An algorithm is presented to be able to select the globally optimal subset of d features from a larger D -feature set. This is a fundamental problem in statistical pattern recognition and combinatorial optimization. Exhaustive enumeration is computationally unfeasible in most applications. This algorithm dynamically searches for the globally optimal solution on a minimum solution tree which is a subtree of the solution tree used in the traditional branch and bound algorithm. The new algorithm is compared theoretically with the branch and bound algorithm. The analysis and the experimental results show that it is more efficient than the traditional algorithm.
34993677
Automatic text location in images and video frames
Abstract Textual data is very important in a number of applications such as image database indexing and document understanding. The goal of automatic text location without character recognition capabilities is to extract image regions that contain only text. These regions can then be either fed to an optical character recognition module or highlighted for a user. Text location is a very difficult problem because the characters in text can vary in font, size, spacing, alignment, orientation, color and texture. Further, characters are often embedded in a complex background in the image. We propose a new text location algorithm that is suitable in a number of applications, including conversion of newspaper advertisements from paper documents to their electronic versions, World Wide Web search, color image indexing and video indexing. In many of these applications, it is not necessary to extract all the text, so we emphasize on extracting important text with large size and high contrast. Our algorithm is very fast and has been shown to be successful in extracting important text in a large number of test images.
10926456
An agent-based approach to knowledge management
Traditional approaches to knowledge management are essentially limited to document management. However, much knowledge in organizations or communities resides in an informal social network and may be accessed only by asking the right people. This paper describes MARS, a multiagent referral system for knowledge management. MARS assigns a software agent to each user. The agents facilitate their users' interactions and help manage their personal social networks. Moreover, the agents cooperate with one another by giving and taking referrals to help their users find the right parties to contact for a specific knowledge need.
14066256
Grid Service Discovery with Rough Sets
The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilizing grid facilities. This paper presents ROSSE, a Rough sets-based search engine for grid service discovery. Building on the Rough sets theory, ROSSE is novel in its capability to deal with the uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct nonfunctional properties related to the quality of service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximize user satisfaction in service discovery. ROSSE is evaluated from the aspects of accuracy and efficiency in discovery of computing services.
8762235
A Three-Layer Virtual Director Model for Supporting Automated Multi-Site Distributed Education
In multi-site distributed education (MSDE), video streams from multiple sites are available. To best utilize the limited screen space at each site, we develop a customizable, automated display management system in this paper, i.e., only user-preferred streams will be shown as triggered by events and timers. The configuration of such user preference, however, is challenging because it has to be both human-friendly and machine-friendly. To address this challenge, we propose a three-layer virtual director model. In the user layer, we identify three categories of parameters that can represent a wide range of user preferences yet are easy to use. These preferences are then automatically translated into a machine-friendly timed automaton in the execution layer. The automaton is simulated dynamically, which selects a subset of streams to show on the screen through a display layer. Evaluation results demonstrate the correctness and efficiency of the proposed framework
18656180
Application of PGA on Optimization of Distribution of Shopping Centers
In this study, the distribution of shopping centers is optimized in terms of realizing the shortest car-based shopping trips in an urban area. Modal split is performed between road and public traffic networks is calculated, and then the interaction between land-use and transportation in the context of choice of shopping destinations is modeled to build the optimal function. Parallel genetic algorithm (PGA) is applied to solve the optimal problem on distribution of the area of shopping centers. Several problems in application of PGA are discussed. A case study is undertaken in order to examine the effectiveness of this method.
1248870
An incentive mechanism for message relaying in unstructured peer-to-peer systems
Distributed message relaying is an important function of a peer-to-peer system to discover service providers. Existing search protocols in unstructured peer-to-peer systems either create huge burden on communications or cause long response time. Moreover, these systems are also vulnerable to the free riding problem. In this paper we present an incentive mechanism that not only mitigates the free riding problem, but also achieves good system efficiency in message relaying for peer discovery. In this mechanism promised rewards are passed along the message propagation process. A peer is rewarded if a service provider is found via a relaying path that includes this peer. We provide some analytic insights to the symmetric Nash equilibrium strategies of this game, and an approximate approach to calculate this equilibrium. Experiments show that this incentive mechanism brings a system utility generally higher than breadth-first search and random walks, based on both the estimated utility from our approximate equilibrium and the utility generated from learning in the incentive mechanism.