{"title":"Evaluation of an interactive tool for handwritten form description","authors":"G. Leedham, D. Monger","doi":"10.1109/ICDAR.1995.602135","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602135","url":null,"abstract":"A highly time-consuming activity in many areas of commerce and business is the manual entry into computer of data handwritten on forms. All forms in widespread use contain discrete fields where specific information can be entered. Automatic recognition of these forms could be achieved using existing state-of-the-art OCR algorithms for numerals, alphabetic characters, cursive words, signatures and mark sensing if they could be rapidly configured along with any inter-relationships and dependencies for different forms. This paper describes an initial implementation of an interactive graphical tool to allow the handwritten fields of a form and their inter-relationships to be described and defined for automatic linking with appropriate OCR algorithms. Results indicate that the main requirement is for the operator to have a full understanding of the handwritten form and an ability to describe its contents.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114235176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A probabilistic approach to automatic handwritten address reading","authors":"J. Bertille, M. Gilloux","doi":"10.1109/ICDAR.1995.599015","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599015","url":null,"abstract":"To sort handwritten mail pieces, the French Postal Office Research Centre has developed a reading device. After recalling the different processing stages of our system, we focus on the problem of merging the decisions made by its different sub-modules (postal code and city name hypotheses) to produce a unique and reliable final decision. To achieve this goal we use a probabilistic modelling of the system behaviour taking into account the characteristics of all the processing stages involved in handwritten address recognition. This approach has been rested on large reference sets consisting of live mail handwritten envelopes and already produces very promising results.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121696741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Four directional adjacency graphs (FDAG) and their application in locating fields in forms","authors":"Jianxing Yuan, Y. Tang, C. Suen","doi":"10.1109/ICDAR.1995.602012","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602012","url":null,"abstract":"A new non-hierarchical spatial data structure named four directional adjacency graphs (FDAG) is proposed. In the FDAG vertical and horizontal neighborhood relationship between rectangles is well represented so that structural information can be easily extracted. An application for structural analysis of forms is given, where experiments are conducted with positive results.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124368685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-lingual, multi-font and multi-size large-set character recognition using self-organizing neural network","authors":"Seong-Whan Lee, Jongyeol Kim","doi":"10.1109/ICDAR.1995.598937","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598937","url":null,"abstract":"We propose a practical scheme for multilingual multi font, and multi size large set character recognition using self organizing neural network. In order to improve the performance of the proposed scheme, a nonlinear shape normalization based on dot density and three kinds of hierarchical features are introduced. For coarse classification, two kinds of classifiers are proposed. One is a hierarchical tree classifier, and the other is a SOFM/LVQ based classifier which is composed of an adaptive SOFM coarse classifier and LVQ4 language classifiers. For fine classification, an LVQ4 classifier has been adopted. In order to evaluate the performance of the proposed scheme, recognition experiments with 3,367,200 characters having 7320 different classes have been carried out on a 486 DX-2 66 MHz PC. Experimental results reveal that the proposed scheme using an adaptive SOFM coarse classifier, LVQ4 language classifiers, and LVQ4 fine classifiers has a high recognition rate of over 98.27% and a fast execution time of more than 40 characters per second.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"512 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127604269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Construction of generic models of document structures using inference of tree grammars","authors":"O. Akindele, A. Belaïd","doi":"10.1109/ICDAR.1995.598977","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598977","url":null,"abstract":"The use of generic model for a document class as the knowledge base in a Document Analysis System facilitates the analysis and understanding of documents belonging to this class. Nevertheless, absence of tools permitting the acquisition of this type of model is an hindrance to the conception of entirely automatic systems. In this paper, we present a method for acquiring the generic model for a document class from document samples belonging to this class. Our method is based on Inference of Tree Grammars and combination of ODA-like generic constructors. The method constructs specific physical structure for each sample and invites the user to assign logical labels to its components. From these logically labeled specific structures, it generates and modifies the generic model for the class under treatment.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121719442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Delta LogNormal theory for the generation and modeling of cursive characters","authors":"W. Guerfali, R. Plamondon","doi":"10.1109/ICDAR.1995.599042","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.599042","url":null,"abstract":"We exploit the Delta LogNormal theory, a powerful tool for the generation and modeling of rapid movements to generate curvilinear strokes and constituting letters that respect both the dynamics and the appearance of movements made by a human. A theoretical analysis of the effects of the various parameters of the model is carried out: first, to reduce the size of the representation space of the letter models; and second, to select the parameters that constitute the optimal conditions for representing various symbols.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132523174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Garcia-Salicetti, B. Dorizzi, P. Gallinari, A. Mellouk, D. Fanchon
{"title":"A hidden Markov model extension of a neural predictive system for on-line character recognition","authors":"S. Garcia-Salicetti, B. Dorizzi, P. Gallinari, A. Mellouk, D. Fanchon","doi":"10.1109/ICDAR.1995.598942","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598942","url":null,"abstract":"The authors present a neural predictive system for on-line writer-independent character recognition. The data collection of each letter contains the pen trajectory information recorded by a digitizing tablet. Each letter is modeled by a fixed number of predictive neural networks (NN), so that a different multilayer NN models successive parts of a letter. The topology of each letter-model only permits transitions from each NN to itself or to its neighbors. In order to deal with the great variability proper to cursive handwriting in the omni-scriptor framework, they implement a holistic approach during both learning and recognition by performing adaptive segmentation. Also, the recognition step implements interactive recognition and segmentation. The approach compares neural techniques combined with dynamic programming to its extension to the hidden Markov model (HMM) framework. The first system gives quite good recognition rates on letter databases obtained from 10 different writers, and results improve considerably when one considers the extension of the first system to the durational HMM framework.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129963748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Power functions and their use in selecting distance functions for document degradation model validation","authors":"T. Kanungo, R. Haralick, H. Baird","doi":"10.1109/ICDAR.1995.602007","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602007","url":null,"abstract":"Two document degradation models that model the perturbations introduced during the document printing and scanning process were proposed recently. Although degradation models are very useful, it is very important that we validate these models by comparing the synthetically generated images against real images. In recent past, two different validation procedures have also been proposed to validate such document degradation models. These validation procedures are functions of sample size and various distance functions. In this paper we outline a statistical methodology to compare the various validation schemes that result by using different distance functions. This methodology is general enough to compare any two validation schemes.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133887331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reading encrypted postal indicia","authors":"Mark Cullen, L. Pintsov, Brian Romansky","doi":"10.1109/ICDAR.1995.602075","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.602075","url":null,"abstract":"The next generation of postal processing equipment will incorporate some method of verifying the postal revenue block (postal indicia) as a means of reducing postal fraud. The introduction of new digital printing technologies necessitates the encryption of revenue block information. This paper presents an approach for the verification process which includes algorithms for reading an encrypted postal indicia. In particular, postal indicia reading is tested for robustness against a variety of printing and media characteristics, and potential defects.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131645729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Column segmentation by white space pattern matching","authors":"M. Ozaki","doi":"10.1109/ICDAR.1995.598960","DOIUrl":"https://doi.org/10.1109/ICDAR.1995.598960","url":null,"abstract":"Model-based column segmentation is described. Sequences of horizontal white space across a column are used as the basic features. Structures of columns in a specific publication are described by two levels of regular expressions: column expressions (CE) and element expressions (EE). Additional spatial constraints for element attributes can be described. A CE represents patterns of element sequences. An EE represents patterns of white space sequences for each element type. Segmentation is performed in three steps: element candidate extraction using EEs, column structure verification using the CE and ranking by comparison with statistical data. Experiments were performed on columns in two different scientific journals. More than 70% of the columns were correctly segmented as the top choice and more than 87% were in the top three choices. When spatial constraints were applied to element attributes, the rate was more than 90%.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131202398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}