作者:
Cote, M.Lecolinet, E.Cheriet, M.Suen, C.Y.Telecom Paris
Departement Signal 46 rue Barrault Paris Cedex 1375634 France E.T.S
Universite du Quebec 4750 Avenue Henri-Julien MontrealQCH2T2C8 Canada CENPARMI
Concordia University 1455 de Maisonneuve West MontrealQC3G1M8 Canada
This paper presents a new perception based model for reading cursive script. We describe the organization of our pseudo-neuronal system and show the role of activation mechanism in perceiving and reading cursive scrip...
recognition methods use different features to assign a pattern to a prototype class. The recognition accuracy strongly depends on the selected features. We present a novel fuzzy methodology to extract appropriate fuzz...
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recognition methods use different features to assign a pattern to a prototype class. The recognition accuracy strongly depends on the selected features. We present a novel fuzzy methodology to extract appropriate fuzzy features from the handwriting data. From these meaningful features a set of linguistic rules are derived which in turn constitute a fuzzy rule base for character recognition. The fuzzy features are confined to their meaningfulness with the help of a multistage feature aggregation scheme.
This article presents a complete hybrid object recognition system for three-dimensional objects using the characteristic view (ChV) idea. To apply the ChV representation method in a recognition system investigations a...
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ISBN:
(纸本)3540606971
This article presents a complete hybrid object recognition system for three-dimensional objects using the characteristic view (ChV) idea. To apply the ChV representation method in a recognition system investigations are needed concerning the processing of large object data bases. First we present two methods to reduce the number of views in the object data base. Second we developed an accumulator (AC)-based matching strategy combined with a localization process. This strategy bases on a hierarchical indexing structure that uses a Gaussian distributed voting. The off-line part of the matching includes a statistical analysis of the object data base and an interface to process results of a sensor configuration analysis. The calculated results support the construction of an adapted layer model suitable for hierarchical indexing. Further an unsupervised learning module is introduced;that investigates the measurement errors and adapts the system online. Results of the matching are verified by a localization tool, which uses an interpretation tree search combined by a shape from angle method and a constrained alignment technique. The article shows results with real greyscale images.
This paper introduces and discusses the concept of stable and shared information and its application in a new modeling method based on the selection of features. The model constructed is used for the automatic detecti...
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This paper introduces and discusses the concept of stable and shared information and its application in a new modeling method based on the selection of features. The model constructed is used for the automatic detection of scriptor-independent information. The selected features are treated as functions in order to allow a continuous interpretation of the script signal. This proposed representation permits the joint interpretation of on-line and off-line information. The paper then goes on to present some experimental results.
The paper presents the algorithms for recognition and beautification which are used in incremental graphic design applications. These applications propose multimodal interfaces integrating handwriting, gesture, and sp...
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The paper presents the algorithms for recognition and beautification which are used in incremental graphic design applications. These applications propose multimodal interfaces integrating handwriting, gesture, and speech on a pen-computer. User and computer collaborate to perform the task of incrementally designing a drawing. Processing and data representation take into account the variable quality of handwritten data, the man-machine interaction context and the cooperation between the user and the interpretation system. Both recognition algorithms may be used in combination in order to increase the speed and the set of recognized figures. Local recognition is followed by the beautification of the global structure in order to detect alignments and logical structures. The beautification enables the user to display a clean version of the original draft. The applications which the authors developed are used to recognize tables, gestures, geometrical figures or diagram networks.
We present a formal model for processing gray-scale images of business forms such as bank cheques. The formal model is based on a new hybrid-based approach namely the base lines. In fact, to segment handwritten and ha...
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We present a formal model for processing gray-scale images of business forms such as bank cheques. The formal model is based on a new hybrid-based approach namely the base lines. In fact, to segment handwritten and hand-printed data from bank cheques, knowledge rules and base lines will have important roles to segment and extract the information from bank cheques. The architectural design as well as the major components of the system is discussed in full detail. Moreover, the significant use of the morphological followed by the topological processing on gray-scale images is used as a major aspect to restore the lost information after the elimination of the background and the base lines from the gray-scale cheques.
Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clu...
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ISBN:
(纸本)0818671289
Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clustering based technique for extracting characters from form documents. In this method, they treat the character extraction process as a pattern clustering problem. The feasibility of the novel method is demonstrated through experimenting various kinds of forms. Experimental results reveal the feasibility of the novel method.
Feature extraction is a crucial part of classification procedures. In this paper we present an approach to utilize feature extraction criteria to predict the potential efficiency of a neural network classifier. Statis...
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Feature extraction is a crucial part of classification procedures. In this paper we present an approach to utilize feature extraction criteria to predict the potential efficiency of a neural network classifier. Statistical and geometrical criteria are introduced for analysis. The complete system of our research consists of a class of generalized Hough-transformations for feature extraction and a subsequent neural network. The neural network performs the classification based on respective features. For an example we concentrated on a patternrecognition problem-the classification of handwritten numerals. As a result of our work we assign two feature extraction criteria to the employed network for a significant estimation of its efficiency.
A method for recognizing unconstrained handwritten words belonging to a small static lexicon is proposed. Our computational theory is based on a psychological model of the reading process of a fast reader. The method ...
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A method for recognizing unconstrained handwritten words belonging to a small static lexicon is proposed. Our computational theory is based on a psychological model of the reading process of a fast reader. The method we propose is global in its nature and avoid the difficult segmentation stage of common wordrecognition techniques. Our computational theory has been applied to the processing of handwritten bank cheques, whose problem domain is that of unconstrained handwriting, unlimited writers in a small static lexicon. Current results seem comparable to those published in the literature and support our computational theory.
The paper describes a holistic recognizer developed for use in a hybrid recognition system. The recognizer uses information about the word shape. As this information is strongly related to word zoning, care is taken t...
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The paper describes a holistic recognizer developed for use in a hybrid recognition system. The recognizer uses information about the word shape. As this information is strongly related to word zoning, care is taken to avoid limitations resulting from the inaccuracy of zone detection. The recognizer uses a very simple set of features and a fuzzy set based pattern matching technique. This aims to increase its robustness, but also causes problems with disambiguation of the results. A verification mechanism, using letter alternatives as compound features, is introduced. The letter alternatives are obtained from a segmentation based recognizer coexisting in the hybrid system. The holistic recognizer is found capable of outperforming the segmentation based one, despite the remaining disambiguation problems. When working together in a hybrid system, the results are significantly higher than those of the individual recognizers. recognition results are reported and compared.
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