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Papers by C. Viard-gaudin

Research paper thumbnail of An Online Hand-Drawn Electric Circuit Diagram Recognition System Using Hidden Markov Models

2008 International Symposium on Information Science and Engineering, 2008

In this paper we experiment the capabilities of Hidden Markov Models (HMM) to model the time-vari... more In this paper we experiment the capabilities of Hidden Markov Models (HMM) to model the time-variant signal produced by the movement of a pen when drawing a sketch such as an electrical circuit diagram. We consider that the sketches have been generated by a two-level stochastic process. The underlying process governs the stroke production from a neuro-motor control point of

Research paper thumbnail of Indexation d ‘une base de données de documents manuscrits Identification du scripteur

Research paper thumbnail of Handwriting Analysis

Research paper thumbnail of First experiments on a new online handwritten flowchart database

Research paper thumbnail of Multi-modular architecture based on convolutional neural networks for online handwritten character recognition

Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., 2002

Research paper thumbnail of Language Models for Handwritten Short Message Services

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

Research paper thumbnail of A Multi-stroke Dynamic Time Warping Distance Based on A* Optimization

2013 12th International Conference on Document Analysis and Recognition, 2013

Dynamic Time Warping (DTW) is a famous distance to compare two mono-stroke symbols. It obeys the ... more Dynamic Time Warping (DTW) is a famous distance to compare two mono-stroke symbols. It obeys the boundary and continuity constraints. The extension to multi-stroke symbols raises specific problems. A naïve solution is to convert the multi-stroke symbol into a single one by a direct concatenation respecting the handwriting order. However, people may write a symbol with different stroke orders and different stroke directions. Applying a brute force method by searching all the possible directions and orders leads to prohibitive calculation times. To reduce the searching complexity, we propose the DTW-A* algorithm that keeps the continuity constraint during each partial matching. This DTW-A* distance achieves the best recognition rate and the best stability in cross-validation when comparing three distances (DTW-A*, DTW, Modified Hausdorff Distance) on a flowchart dataset which mainly contains multi-stroke symbols.

Research paper thumbnail of Integration of shape context et neural networks for symbol recognition

Research paper thumbnail of SCUT-COUCH Textline_NU: An Unconstrained Online Handwritten Chinese Text Lines Dataset

2010 12th International Conference on Frontiers in Handwriting Recognition, 2010

Research paper thumbnail of <title>Retrieving handwriting by combining word spotting and manifold ranking</title>

Document Recognition and Retrieval XIX, 2012

ABSTRACT Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequenc... more ABSTRACT Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequence of points (x, y). As the amount of data available in this form increases, algorithms for retrieval of online data are needed. Word spotting is a common approach used for the retrieval of handwriting. However, from an information retrieval (IR) perspective, word spotting is a primitive keyword based matching and retrieval strategy. We propose a framework for handwriting retrieval where an arbitrary word spotting method is used, and then a manifold ranking algorithm is applied on the initial retrieval scores. Experimental results on a database of more than 2,000 handwritten newswires show that our method can improve the performances of a state-of-the-art word spotting system by more than 10%.

Research paper thumbnail of Lexicon-Based Word Recognition Using Support Vector Machine and Hidden Markov Model

2009 10th International Conference on Document Analysis and Recognition, 2009

Research paper thumbnail of Language independent statistical models for on-line handwriting recognition

Research paper thumbnail of Two-cost stroke segment grouping mechanism for off-line cursive hand-written word recognition

Research paper thumbnail of An offline cursive handwritten word recognition system

Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology. TENCON 2001 (Cat. No.01CH37239)

Research paper thumbnail of Lecture de codes-barres par vision 2D

Une alternative a l'emploi de la technologie laser pour la realisation de lecteurs de codes-b... more Une alternative a l'emploi de la technologie laser pour la realisation de lecteurs de codes-barres est presentee dans cet article, la solution proposee est basee sur une approche par traitement d'image. On a developpe pour cela un systeme global comportant deux fonctions principales: la localisation du code-barres dans l'image, puis son decodage prenant en compte l'ensemble des pixels du code-barres. La localisation est realisee grâce a une methode originale d'extraction de regions denses en gradients mono-orientes. La lecture est basee sur la detection des transitions entre barres par extraction des passages par zero de la derivee seconde du profil de projection reconstruit a partir de l'image. Ce systeme a ete evalue sur une base de plusieurs centaines d'images, les resultats obtenus montrent un taux de reussite global (localisation et lecture) de 100 % sur une tres large plage de variation des parametres d'acquisition, notamment la resolution et le...

Research paper thumbnail of Offline Cursive Handwriting Recognition System based on Hybrid Markov Model and Neural Networks

An offline cursive handwriting recognition system, based on hybrid of Neural Networks (NN) and Hi... more An offline cursive handwriting recognition system, based on hybrid of Neural Networks (NN) and Hidden Markov Models (HMM), is described in this paper. Applying SegRec principle, the recognizer does not make hard decision at the character segmentation process. Instead, it delays the character segmentation to the recognition stage by generating a segmentation graph that describes all possible ways to segment a word into letters. To recognize a word, the NN computes the observation probabilities for each segmentation candidates (SCs) in the segmentation graph. Then, using concatenated letter-HMMs, a likelihood is computed for each word in the lexicon by multiplying the probabilities over the best paths through the graph. We present in detail two approaches to train the word recognizer: 1). character-level training 2). word-level training. The recognition performances of the two systems are discussed. I.

Research paper thumbnail of The Comparative Study of SVM Tools for Data Classification

Support vector machine (SVM) is one of the recent methods for statistical learning, it addresses ... more Support vector machine (SVM) is one of the recent methods for statistical learning, it addresses classification and regression problems . It can be considered as an alternative to neural networks. The advantage of SVM, with respect to neural network, is that it provides a theoretical framework for taking into account not only the experimental data to design an optimal classifier, but also a structural behavior for allowing better generalization capability. This paper introduces SVM theory, applications and its algorithmic implementations. Although there are proven algorithms for constructing SVM programs, it is usually faster and also more reliable to make use or adapt a public domain SVM implementation packages. In this paper, we explain three of the popularly used C/C++ based SVM packages and demonstrate their usage. We report some results of their usage in classification on a number of different datasets, taking into consideration the tuning of SVM kernel hyperparameters for perf...

Research paper thumbnail of Off-Line Handwriting Modeling as a Trajectory Tracking Problem

Series in Machine Perception and Artificial Intelligence, 1999

Research paper thumbnail of A two-dimensional bar code reader

… Processing, Proceedings of the …, 1994

... section of the bar code, a vision-based reader could reconstruct an average section using the... more ... section of the bar code, a vision-based reader could reconstruct an average section using the whole code area. This is the principle of the proposed approach namely the projection of thebar code&#x27;s image to a one-dimensional signal followed by the signal processing and its ...

Research paper thumbnail of Online text independent writer identification using character prototypes distribution

Research paper thumbnail of An Online Hand-Drawn Electric Circuit Diagram Recognition System Using Hidden Markov Models

2008 International Symposium on Information Science and Engineering, 2008

In this paper we experiment the capabilities of Hidden Markov Models (HMM) to model the time-vari... more In this paper we experiment the capabilities of Hidden Markov Models (HMM) to model the time-variant signal produced by the movement of a pen when drawing a sketch such as an electrical circuit diagram. We consider that the sketches have been generated by a two-level stochastic process. The underlying process governs the stroke production from a neuro-motor control point of

Research paper thumbnail of Indexation d ‘une base de données de documents manuscrits Identification du scripteur

Research paper thumbnail of Handwriting Analysis

Research paper thumbnail of First experiments on a new online handwritten flowchart database

Research paper thumbnail of Multi-modular architecture based on convolutional neural networks for online handwritten character recognition

Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., 2002

Research paper thumbnail of Language Models for Handwritten Short Message Services

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

Research paper thumbnail of A Multi-stroke Dynamic Time Warping Distance Based on A* Optimization

2013 12th International Conference on Document Analysis and Recognition, 2013

Dynamic Time Warping (DTW) is a famous distance to compare two mono-stroke symbols. It obeys the ... more Dynamic Time Warping (DTW) is a famous distance to compare two mono-stroke symbols. It obeys the boundary and continuity constraints. The extension to multi-stroke symbols raises specific problems. A naïve solution is to convert the multi-stroke symbol into a single one by a direct concatenation respecting the handwriting order. However, people may write a symbol with different stroke orders and different stroke directions. Applying a brute force method by searching all the possible directions and orders leads to prohibitive calculation times. To reduce the searching complexity, we propose the DTW-A* algorithm that keeps the continuity constraint during each partial matching. This DTW-A* distance achieves the best recognition rate and the best stability in cross-validation when comparing three distances (DTW-A*, DTW, Modified Hausdorff Distance) on a flowchart dataset which mainly contains multi-stroke symbols.

Research paper thumbnail of Integration of shape context et neural networks for symbol recognition

Research paper thumbnail of SCUT-COUCH Textline_NU: An Unconstrained Online Handwritten Chinese Text Lines Dataset

2010 12th International Conference on Frontiers in Handwriting Recognition, 2010

Research paper thumbnail of <title>Retrieving handwriting by combining word spotting and manifold ranking</title>

Document Recognition and Retrieval XIX, 2012

ABSTRACT Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequenc... more ABSTRACT Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequence of points (x, y). As the amount of data available in this form increases, algorithms for retrieval of online data are needed. Word spotting is a common approach used for the retrieval of handwriting. However, from an information retrieval (IR) perspective, word spotting is a primitive keyword based matching and retrieval strategy. We propose a framework for handwriting retrieval where an arbitrary word spotting method is used, and then a manifold ranking algorithm is applied on the initial retrieval scores. Experimental results on a database of more than 2,000 handwritten newswires show that our method can improve the performances of a state-of-the-art word spotting system by more than 10%.

Research paper thumbnail of Lexicon-Based Word Recognition Using Support Vector Machine and Hidden Markov Model

2009 10th International Conference on Document Analysis and Recognition, 2009

Research paper thumbnail of Language independent statistical models for on-line handwriting recognition

Research paper thumbnail of Two-cost stroke segment grouping mechanism for off-line cursive hand-written word recognition

Research paper thumbnail of An offline cursive handwritten word recognition system

Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology. TENCON 2001 (Cat. No.01CH37239)

Research paper thumbnail of Lecture de codes-barres par vision 2D

Une alternative a l'emploi de la technologie laser pour la realisation de lecteurs de codes-b... more Une alternative a l'emploi de la technologie laser pour la realisation de lecteurs de codes-barres est presentee dans cet article, la solution proposee est basee sur une approche par traitement d'image. On a developpe pour cela un systeme global comportant deux fonctions principales: la localisation du code-barres dans l'image, puis son decodage prenant en compte l'ensemble des pixels du code-barres. La localisation est realisee grâce a une methode originale d'extraction de regions denses en gradients mono-orientes. La lecture est basee sur la detection des transitions entre barres par extraction des passages par zero de la derivee seconde du profil de projection reconstruit a partir de l'image. Ce systeme a ete evalue sur une base de plusieurs centaines d'images, les resultats obtenus montrent un taux de reussite global (localisation et lecture) de 100 % sur une tres large plage de variation des parametres d'acquisition, notamment la resolution et le...

Research paper thumbnail of Offline Cursive Handwriting Recognition System based on Hybrid Markov Model and Neural Networks

An offline cursive handwriting recognition system, based on hybrid of Neural Networks (NN) and Hi... more An offline cursive handwriting recognition system, based on hybrid of Neural Networks (NN) and Hidden Markov Models (HMM), is described in this paper. Applying SegRec principle, the recognizer does not make hard decision at the character segmentation process. Instead, it delays the character segmentation to the recognition stage by generating a segmentation graph that describes all possible ways to segment a word into letters. To recognize a word, the NN computes the observation probabilities for each segmentation candidates (SCs) in the segmentation graph. Then, using concatenated letter-HMMs, a likelihood is computed for each word in the lexicon by multiplying the probabilities over the best paths through the graph. We present in detail two approaches to train the word recognizer: 1). character-level training 2). word-level training. The recognition performances of the two systems are discussed. I.

Research paper thumbnail of The Comparative Study of SVM Tools for Data Classification

Support vector machine (SVM) is one of the recent methods for statistical learning, it addresses ... more Support vector machine (SVM) is one of the recent methods for statistical learning, it addresses classification and regression problems . It can be considered as an alternative to neural networks. The advantage of SVM, with respect to neural network, is that it provides a theoretical framework for taking into account not only the experimental data to design an optimal classifier, but also a structural behavior for allowing better generalization capability. This paper introduces SVM theory, applications and its algorithmic implementations. Although there are proven algorithms for constructing SVM programs, it is usually faster and also more reliable to make use or adapt a public domain SVM implementation packages. In this paper, we explain three of the popularly used C/C++ based SVM packages and demonstrate their usage. We report some results of their usage in classification on a number of different datasets, taking into consideration the tuning of SVM kernel hyperparameters for perf...

Research paper thumbnail of Off-Line Handwriting Modeling as a Trajectory Tracking Problem

Series in Machine Perception and Artificial Intelligence, 1999

Research paper thumbnail of A two-dimensional bar code reader

… Processing, Proceedings of the …, 1994

... section of the bar code, a vision-based reader could reconstruct an average section using the... more ... section of the bar code, a vision-based reader could reconstruct an average section using the whole code area. This is the principle of the proposed approach namely the projection of thebar code&#x27;s image to a one-dimensional signal followed by the signal processing and its ...

Research paper thumbnail of Online text independent writer identification using character prototypes distribution