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Статті в журналах з теми "Reconnaissance optique de texte":
Nguyen, Mai Nhu, Catherine S. Fichten, Jillian Budd, Laura King, Maria Barile, Alice Havel, Zohra Mimouni, et al. "Les technologies de l’information et de la communication (TIC) pour soutenir l’autodétermination des étudiants postsecondaires ayant des troubles d’apprentissage (TA)." Développement Humain, Handicap et Changement Social 21, no. 1 (February 18, 2022): 97–110. http://dx.doi.org/10.7202/1086496ar.
Larroque, Tiphaine. "Moments de voyage ou l’expérience d’un espace potentiel : « Parc Central » de Dominique Gonzalez-Foerster." Source(s) – Arts, Civilisation et Histoire de l’Europe, no. 6 (October 19, 2022): 81–97. http://dx.doi.org/10.57086/sources.352.
Abaynarh, Mohammed, Hakim El Fadili, and Lahbib Zenkouar. "Reconnaissance optique de documents amazighes : approches et évaluation des performances." Études et Documents Berbères N° 34, no. 1 (January 23, 2015): 189–98. http://dx.doi.org/10.3917/edb.034.0189.
Vergniault, Christophe, Edouard Buchoud, Joséphine Boisson-Gaboriau, and Amélie Hallier. "Application des méthodes géophysiques pour le diagnostic de l’aléa cavités sur des ouvrages de grands linéaires, en contexte ferroviaire et hydraulique." Revue Française de Géotechnique, no. 172 (2022): 3. http://dx.doi.org/10.1051/geotech/2022006.
Brehl, Medardus, Mihran Dabag, and Alice Volkwein. "Le long chemin vers la « reconnaissance ». Le génocide des arméniens dans le discours politique de la RFA." Guerres mondiales et conflits contemporains N° 292, no. 4 (December 1, 2023): 63–77. http://dx.doi.org/10.3917/gmcc.292.0063.
Boujday, Souhir, and Michèle Salmain. "Nanoparticules d’or pour les biocapteurs : lecture optique de la reconnaissance moléculaire." Photoniques, no. 106 (January 2021): 39–43. http://dx.doi.org/10.1051/photon/202110639.
Spehner, Jean-Claude. "La reconnaissance des facteurs d'un mot dans un texte." Theoretical Computer Science 48 (1986): 35–52. http://dx.doi.org/10.1016/0304-3975(86)90082-4.
Monteiro, A. Reis. "Éducation et reconnaissance chez Françoise Dolto." Hors-thème, no. 11 (July 14, 2010): 80–100. http://dx.doi.org/10.7202/044123ar.
Roseberry, Philippe. "Violence de masse et sécession comme réparation : le cas du Kosovo1." Articles 39, no. 2 (January 29, 2013): 421–34. http://dx.doi.org/10.7202/1013695ar.
Kasprzyk, Damian. "Régionalisme polonais – inspirations françaises. Reconnaissance." Zeszyty Wiejskie 29 (December 5, 2023): 7–25. http://dx.doi.org/10.18778/1506-6541.29.01.
Дисертації з теми "Reconnaissance optique de texte":
Mullot, Rémy. "Segmentation d'images et extraction de primitives pour la reconnaissance optique de texte." Rouen, 1991. http://www.theses.fr/1991ROUES001.
Vincent, Nicole. "Contribution à la reconnaissance de textes multipolices." lyon, INSA, 1988. http://www.theses.fr/1988ISAL0011.
Namane, Abderrahmane. "Degraded printed text and handwritten recognition methods : Application to automatic bank check recognition." Université Louis Pasteur (Strasbourg) (1971-2008), 2007. http://www.theses.fr/2007STR13048.
Character recognition is a significant stage in all document recognition systems. Character recognition is considered as an assignment problem and decision of a given character, and is an active research subject in many disciplines. This thesis is mainly related to the recognition of degraded printed and handwritten characters. New solutions were brought to the field of document image analysis (DIA). The first solution concerns the development of two recognition methods for handwritten numeral character, namely, the method based on the use of Fourier-Mellin transform (FMT) and the self-organization map (SOM), and the parallel combination of HMM-based classifiers using as parameter extraction a new projection technique. In the second solution, one finds a new holistic recognition method of handwritten words applied to French legal amount. The third solution presents two recognition methods based on neural networks for the degraded printed character applied to the Algerian postal check. The first work is based on sequential combination and the second used a serial combination based mainly on the introduction of a relative distance for the quality measurement of the degraded character. During the development of this thesis, methods of preprocessing were also developed, in particular, the handwritten numeral slant correction, the handwritten word central zone detection and its slope
Saidane, Zohra. "Reconnaissance de texte dans les images et les vidéos en utilisant les réseaux de neurones à convolutions." Phd thesis, Télécom ParisTech, 2008. http://pastel.archives-ouvertes.fr/pastel-00004685.
Minetto, Rodrigo. "Reconnaissance de zones de texte et suivi d'objets dans les images et les vidéos." Paris 6, 2012. http://www.theses.fr/2012PA066108.
In this thesis we address three computer vision problems: (1) the detection and recognition of flat text objects in images of real scenes; (2) the tracking of such text objects in a digital video; and (3) the tracking an arbitrary three-dimensional rigid object with known markings in a digital video. For each problem we developed innovative algorithms, which are at least as accurate and robust as other state-of-the-art algorithms. Specifically, for text recognition we developed (and extensively evaluated) a new HOG-based descriptor specialized for Roman script, which we call T-HOG, and showed its value as a post-filter for an existing text detector (SnooperText). We also improved the SnooperText algorithm by using the multi-scale technique to handle widely different letter sizes while limiting the sensitivity of the algorithm to various artifacts. For text tracking, we describe four basic ways of combining a text detector and a text tracker, and we developed a specific tracker based on a particle-filter which exploits the T-HOG recognizer. For rigid object tracking we developed a new accurate and robust algorithm (AFFTrack) that combines the KLT feature tracker with an improved camera calibration procedure. We extensively tested our algorithms on several benchmarks well-known in the literature. We also created benchmarks (publicly available) for the evaluation of text detection and tracking and rigid object tracking algorithms
Paquet, Thierry. "Segmentation et classification de mots en reconnaissance optique de textes manuscrits." Rouen, 1992. http://www.theses.fr/1992ROUES007.
Henry, Jean-Luc. "Reconnaissance et contexte : une approche coopérative pour la lecture de textes imprimés." Lyon, INSA, 1996. http://www.theses.fr/1996ISAL0027.
The printed documents analysis is not only based on the optical character recognition, it also uses statistical, typographic and contextual information. A contextual stage, independent from the recognition does not give good results. The topic of this work is to build a cooperation between the recognition and the contextual stage. The recognition stage give information to the syntactic analysis stage in order to improve the correction process. Then, the contextual analysis stage provides necessary information to the recognition stage in order to correct its decision criteria and to improve automatically the recognition performance during the reading. This work is divided in two parts. The first part presents the character recognition only from the patterns and the second part studies the recognition with the help of contextual information mainly based on a syntactic correction. This work starts with a presentation of classic methods to extract features from patterns and to compare features descriptions. Then we introduce a pattern compacted by mutually comparing characters to collect all identical patterns on the entire text, called prototypes. In order to reconstruct the recognized text, we identify these prototypes with an original pretopological recognition approach, based on a classification by adaptive neighborhoods. The second part of this work deals with the contextual processing and the cooperation abilities between the two main stages involved in the recognition process. The contextual analysis corrects recognition errors with the pattern redundancies information and a trie dictionary. The system reorganizes pattern representation of the system by modifying parameters that intervene in the process of recognition. The global recognition rate reach an optimum that no longer depends on the training set, but on choice of features and the method of comparison used
Soua, Mahmoud. "Extraction hybride et description structurelle de caractères pour une reconnaissance efficace de texte dans les documents hétérogènes scannés : Méthodes et Algorithmes parallèles." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1069/document.
The Optical Character Recognition (OCR) is a process that converts text images into editable text documents. Today, these systems are widely used in the dematerialization applications such as mail sorting, bill management, etc. In this context, the aim of this thesis is to propose an OCR system that provides a better compromise between recognition rate and processing speed which allows to give a reliable and a real time documents dematerialization. To ensure its recognition, the text is firstly extracted from the background. Then, it is segmented into disjoint characters that are described based on their structural characteristics. Finally, the characters are recognized when comparing their descriptors with a predefined ones.The text extraction, based on binarization methods remains difficult in heterogeneous and scanned documents with a complex and noisy background where the text may be confused with a textured background or because of the noise. On the other hand, the description of characters, and the extraction of segments, are often complex using calculation of geometricaltransformations, polygon, including a large number of characteristics or gives low discrimination if the characteristics of the selected type are sensitive to variation of scale, style, etc. For this, we adapt our algorithms to the type of heterogeneous and scanned documents. We also provide a high discriminatiobn between characters that descriptionis based on the study of the structure of the characters according to their horizontal and vertical projections. To ensure real-time processing, we parallelise algorithms developed on the graphics processor (GPU). Our main contributions in our proposed OCR system are as follows:A new binarisation method for heterogeneous and scanned documents including text regions with complex or homogeneous background. In this method, an image analysis process is used followed by a classification of the document areas into images (text with a complex background) and text (text with a homogeneous background). For text regions is performed text extraction using a hybrid method based on classification algorithm Kmeans (CHK) that we have developed for this aim. This method combines local and global approaches. It improves the quality of separation text/background, while minimizing the amount of distortion for text extraction from the scanned document and noisy because of the process of digitization. The image areas are improved with Gamma Correction (CG) before applying HBK. According to our experiment, our text extraction method gives 98% of character recognition rate on heterogeneous scanned documents.A Unified Character Descriptor based on the study of the character structure. It employs a sufficient number of characteristics resulting from the unification of the descriptors of the horizontal and vertical projection of the characters for efficient discrimination. The advantage of this descriptor is both on its high performance and its simple computation. It supports the recognition of alphanumeric and multiscale characters. The proposed descriptor provides a character recognition 100% for a given Face-type and Font-size.Parallelization of the proposed character recognition system. The GPU graphics processor has been used as a platform of parallelization. Flexible and powerful, this architecture provides an effective solution for accelerating intensive image processing algorithms. Our implementation, combines coarse/fine-grained parallelization strategies to speed up the steps of the OCR chain. In addition, the CPU-GPU communication overheads are avoided and a good memory management is assured. The effectiveness of our implementation is validated through extensive experiments
Wolf, Christian. "Détection de textes dans des images issues d'un flux vidéo pour l'indexation sémantique." Lyon, INSA, 2003. http://theses.insa-lyon.fr/publication/2003ISAL0074/these.pdf.
This work situates within the framework of image and video indexation. A way to include semantic knowledge into the indexing process is to use the text included in the images and video sequences. It is rich in information but easy to use. Existing methods for text detection are simple: most of them are based on texture estimation or edge detection followed by an accumulation of these characteristics. We suggest the usage of geometrical features very early in the detection chain: a first coarse detection calculates a text "probability" image. Afterwards, for each pixel we calculate geometrical properties of the eventual surrounding text rectangle, which are added to the features of the first step and fed into a support vector machine classifier. For the application to video sequences, we propose an algorithm which detects text on a frame by frame basis, tracking the found text rectangles across multiple frames and integrating the frame robustly into a single image. We tackle the character segmentation problem and suggest two different methods: the first algorithm maximizes a criterion based on the local contrast in the image. The second approach exploits a priori knowledge on the spatial binary distribution of the pixels. This prior knowledge in the form of a Markov random field model is integrated into Bayesian estimation framework in order to obtain an estimation of the original binary image
Nosary, Ali. "Reconnaissance automatique de textes manuscrits par adaptation au scripteur." Rouen, 2002. http://www.theses.fr/2002ROUES007.
This thesis deals with the problem of off-line handwritten text recognition. It describes a system of text recognition which exploits an original principle of adaptation to the handwriting to be recognized. The adaptation principle, inspired by contextual effects observed from a human reader, is based on the automatic learning, during the recognition, of the graphical characteristics of the handwriting (writer invariants). The word recognition proceeds according to an analytical approach based on a segmentation-recognition principle. The on-line adaptation of the recognition system relies on the iteration of two steps : a word recognition step which allows to label the writer's representations (allographes) on the whole text and a revaluation step of character models. The implementation of our adaptation strategy requires an interactive recognition scheme able to make interact treatments at various contextual levels. The interaction model retained is based on the multi-agent paradigm
Книги з теми "Reconnaissance optique de texte":
Symposium, DAGM (Organization). Pattern recognition: 26th DAGM symposium, Tübingen, Germany, August 30-September 1, 2004 : proceedings. Berlin: Springer, 2004.
Symposium, DAGM (Organization). Pattern recognition: 29th DAGM symposium, Heidelberg, Germany, September 12-14, 2007 : proceedings. Berlin: Springer, 2007.
David, Forsyth, ed. Shape, contour, and grouping in computer vision. Berlin: Springer, 1999.
David, Forsyth, ed. Shape, contour, and grouping in computer vision. New York: Springer, 1999.
David, Forsyth, ed. Shape, contour, and grouping in computer vision. Berlin: Springer, 1999.
ICIAR 2006 (2006 Póvoa de Varzim, Portugal). Image analysis and recognition: Third international conference, ICIAR 2006, Póvoa de Varzim, Portugal, September 18-20, 2006 : proceedings. Berlin: Springer, 2006.
Jean-Michel, Jolion, and Kropatsch W, eds. Graph based representations in pattern recognition. Wien: Springer, 1998.
Evison, Martin Paul. Computer-aided forensic facial comparison. Boca Raton, FL: Taylor & Francis Group, 2010.
Jarczyk, Gwendoline. Les premiers combats de la reconnaissance: Maîtrise et servitude dans la "Phénoménologie de l'esprit" de Hegel : texte et commentaire. [Paris]: Aubier, 1987.
Descartes, René. Discours de la méthode: Texte intégral. Paris: Hatier, 1990.
Частини книг з теми "Reconnaissance optique de texte":
Silberztein, Max. "Reconnaissance automatique des mots d’un texte." In Lingvisticæ Investigationes Supplementa, 81. Amsterdam: John Benjamins Publishing Company, 1995. http://dx.doi.org/10.1075/lis.17.08sil.
Spehner, Jean-Claude. "La Reconnaissance Des Facteurs D'un Langage Fini Dans Un Texte En Temps Lineaire - Resume -." In Automata, Languages and Programming, 547–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-19488-6_141.
"Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 153–60. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_008.
"Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 429–35. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_014.
"Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 423–27. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_013.
"Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 437–523. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_015.
"Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 359–419. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_011.
"Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 161–335. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_009.
Rashed, Roshdi. "Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 649–701. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_022.
Rashed, Roshdi. "Texte et Traduction." In Oeuvres philosophiques et scientifiques d'al-Kindī, Volume 1 Optique et la Catoptrique, 571–645. BRILL, 1997. http://dx.doi.org/10.1163/9789004450462_020.
Тези доповідей конференцій з теми "Reconnaissance optique de texte":
Valle, Andrea. "« Mettre au monde le monde ».. Sur la relation entre sémiotique de la production et production sémiotique." In Arts du faire : production et expertise. Limoges: Université de Limoges, 2009. http://dx.doi.org/10.25965/as.3213.