the proposed feedback-based approach is implemented in two steps. In the first step, segmentation is done according to the structural features between the connected components in the legal amounts. In the second step,...
ISBN:
(纸本)0769512631
the proposed feedback-based approach is implemented in two steps. In the first step, segmentation is done according to the structural features between the connected components in the legal amounts. In the second step, a feedback process is introduced to re-segment the parts that could not be identified in the first step. then a multiple neural network classifier is used to verify the re-segmentation result. the confidence value produced by the classifier is used to determine the best segmentation points. this approach is tested on a new CENPARMI database and the result indicates that the correct segmentation rate increased by 13.4% from the previous approach.
Although promising results on the combination of character recognizers have been reported recently, the combination strategies can not be readily applied to the recognition of character strings due to m-n corresponden...
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ISBN:
(纸本)0769512631
Although promising results on the combination of character recognizers have been reported recently, the combination strategies can not be readily applied to the recognition of character strings due to m-n correspondence problems caused by segmentation errors. In this paper, we propose a new paradigm of combining multiple string recognizers and contribute a generic framework for off-line combination. We designed and implemented a graph based off-line combination system, StrCombo, which has achieved a substantial improvement over any one of the individual recognizers in a real-life application. this open combination system provides the possibility of further improving the performance of string recognizers when new recognizers and combination rules are available.
this paper investigates dynamic handwritten signature verification (HSV) using the wavelet transform with verification by the backpropagation neural network (NN). It is yet another avenue in the approach to HS V that ...
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ISBN:
(纸本)0769512631
this paper investigates dynamic handwritten signature verification (HSV) using the wavelet transform with verification by the backpropagation neural network (NN). It is yet another avenue in the approach to HS V that is found to produce excellent results when compared with other methods of dynamic, or on-line, HSV. Using a database of dynamic signatures collected from 41 Chinese writers and 7 from Latin script we extract features (including pen pressure, x and y velocity, angle of pen movement and angular velocity) from the signature and apply the Daubechies-6 wavelet transform using coefficients as input to a NN which learns to verify signatures with a False Rejection Rate (FRR) of 0.0% and False Acceptance Rate (FAR) less of than 0.1%.
this paper deals with an Optical Character recognition system for printed Oriya, a popular Indian script. the development of OCR for this script is difficult because a large number of characters have to be recognized....
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ISBN:
(纸本)0769512631
this paper deals with an Optical Character recognition system for printed Oriya, a popular Indian script. the development of OCR for this script is difficult because a large number of characters have to be recognized. In the proposed system, the digitized document image is first passed through preprocessing modules like skew correction, line segmentation, :,one detection, word and character segmentation, etc. these modules have been developed by combining some conventional techniques with some newly proposed ones. Next, individual characters are recognized using a combination of stroke and run-number based features, along with features obtained from the concept of a water reservoir the feature detection methods are simple and robust. A prototype of the system has been tested on a variety of printed Oriya material, and currently achieves 96.3% character level accuracy on average.
this paper presents newly developed segmentation algorithm based on k-NN statistical patternrecognition rule. this algorithm uses arbitrary surface description as the primitives and can be described as region growing...
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ISBN:
(纸本)9665530798
this paper presents newly developed segmentation algorithm based on k-NN statistical patternrecognition rule. this algorithm uses arbitrary surface description as the primitives and can be described as region growing method.
the structure of mathematics notation is particularly difficult to recognize in handwritten notation because irregular symbol placements are common. We present an efficient and robust method of parsing handwritten and...
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ISBN:
(纸本)0769512631
the structure of mathematics notation is particularly difficult to recognize in handwritten notation because irregular symbol placements are common. We present an efficient and robust method of parsing handwritten and typeset mathematics notation without backtracking. the system is designed to be easily adaptable to various dialects of mathematics notation. the following strategies are used: (1) separate the analysis of layout, syntax, and semantics, (2) recursively apply search functions and image partitioning to recognize dominant and nested baselines, and (3) use tree transformations to express computations in a compact, efficiently executable form.
It is quite common in document analysis and symbol recognition to rely on a priori knowledge about the nature of the document in order to locate candidate symbols [3]. It is desirable, but less common, for a segmentat...
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ISBN:
(纸本)0769512631
It is quite common in document analysis and symbol recognition to rely on a priori knowledge about the nature of the document in order to locate candidate symbols [3]. It is desirable, but less common, for a segmentation procedure to rely on "a posteriori" feedback from a non-human-guided process to adjust for segmentation errors. For this method to succeed, the feedback must come from a reliable classifier (one that is able to reject negative symbols including miss-segmented symbols) [1]. this paper examines the use of positive and negative training data on a nearest-neighbour classifier for hand-drawn geometric shapes. We explore the issues involved in the development of a reliable classifier using this method, and we discuss the trade-off between reliability and correctness.
Unified Modeling Language (UML) diagrams are widely used by software engineers to describe the structure of software systems. Early in the software design cycle, software engineers informally sketch initial UML diagra...
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ISBN:
(纸本)0769512631
Unified Modeling Language (UML) diagrams are widely used by software engineers to describe the structure of software systems. Early in the software design cycle, software engineers informally sketch initial UML diagrams on paper or whiteboards. the information provided by these UML diagrams needs to be made available to Computer Assisted Software Engineering (CASE) tools. In order to smooththis transition from paper to electronic form, we have developed an on-line recognition system for UML diagrams. the system accepts input from an electronic whiteboard, a data tablet or a mouse. Efforts have been made to separate the domain-independent and domain-specific parts of the recognition system. the Kernel of the system is retargetable, providing a general front end for on-line recognition of any glyph-based diagram notation. the Kernel is extended with UML-specific routines for segmentation, recognition of glyphs, and recognition of glyph relationships.
this paper presents the results of the First international Newspaper Segmentation contest that was organized on the frame of ICDAR'2001 conference. the aim of this contest was to evaluate all existing algorithms f...
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ISBN:
(纸本)0769512631
this paper presents the results of the First international Newspaper Segmentation contest that was organized on the frame of ICDAR'2001 conference. the aim of this contest was to evaluate all existing algorithms for document image segmentation that can be applied to Newspaper page segmentation. We evaluated the performance of three different newspaper segmentation algorithms on tracing all basic entities that appear in newspaper pages from the beginning of the previous century up to the present. the selected entities are text regions, lines and images/drawings. Both training and test sets come,from Greek and English newspapers. the performance evaluation method is based on counting the number of matches between the entities detected by the algorithms and the entities of the ground truth. In order to rank the global performance of each participant, we employed a metric that combines the average values of detection rate and recognition accuracy.
In imitation learning processes, the "student" robot must be able to perceive the environment and to detect one "teacher". In our approach of learning by imitation, we consider that the student tri...
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