Florent Montreuil, Stéphane Nicolas, E. Grosicki, L. Heutte
{"title":"A New Hierarchical Handwritten Document Layout Extraction Based on Conditional Random Field Modeling","authors":"Florent Montreuil, Stéphane Nicolas, E. Grosicki, L. Heutte","doi":"10.1109/ICFHR.2010.13","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.13","url":null,"abstract":"In this study we describe a new approach to extract layout of unconstrained handwritten letters such as those sent by individuals to companies. The proposed model uses a hierarchical combination of Conditional Random Fields (CRFs) which gives access to various levels of the layout interpretation. The analysis proceeds by decreasing the resolution and increasing the abstraction of the document, starting from high resolution analysis (pixel level), to a low resolution of the layout structure. Informations of high resolution are used to bring a specific prior knowledge of the layout like presence of textual information. Experiments have been performed on the RIMES database composed of more than 5000 handwritten letters. Good results have been reported showing the capacity of our approach to extract simultaneously the physical and logical layouts.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126584624","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":"JollyMate: Assistive Technology for Young Children with Dyslexia","authors":"Jignesh Khakhar, S. Madhvanath","doi":"10.1109/ICFHR.2010.95","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.95","url":null,"abstract":"In this paper, we describe Jolly mate, a product concept that we have envisioned as assistive technology for young children with Dyslexia. Jolly mate, a digital notepad, emulates the Jolly Phonics system of teaching letter sounds and letter formation to children with dyslexia. Jolly mate in turn uses simple handwritten character recognizers created using the Lipi IDE tool from the Lipi Toolkit project, for detecting when a character has been written incorrectly. In this paper we describe the Jolly mate concept in brief, the Lipi IDE tool used to create the recognizers, and their integration.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129220462","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}
M. Liwicki, S. Uchida, M. Iwamura, S. Omachi, K. Kise
{"title":"Embedding Meta-Information in Handwriting -- Reed-Solomon for Reliable Error Correction","authors":"M. Liwicki, S. Uchida, M. Iwamura, S. Omachi, K. Kise","doi":"10.1109/ICFHR.2010.127","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.127","url":null,"abstract":"In this paper a more compact and more reliable coding scheme for the data-embedding pen is proposed. The data-embedding pen produces an additional ink-dot sequence along a handwritten pattern during writing. The ink-dot sequence represents, for example, meta-information (such as the writer’s name and the date of writing) and thus drastically increases the value of the handwriting on a physical paper. There is no need to get access to any memory on the pen to recover the information, which is especially useful in multi-writer or multi-pen scenarios. In this paper we focus on the compactness of the encoded information. The aim of this paper is to encode as much information as possible in short stroke sequences. In our experiments we show that we can embed more information in shorter strokes than in previous work. In straight lines as short as 5 cm, 32 bits can successfully be embedded. Furthermore, the new encoding scheme also works reliably on more complex patterns.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"17 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133170532","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}
Mudit Agrawal, Alexander Zotov, Ming Ye, Sashi Raghupathy
{"title":"Context Aware On-line Diagramming Recognition","authors":"Mudit Agrawal, Alexander Zotov, Ming Ye, Sashi Raghupathy","doi":"10.1109/ICFHR.2010.124","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.124","url":null,"abstract":"This paper presents a context aware, online immediate-mode diagramming recognition and beautification software for hand-sketched diagrams. The system is independent of stroke-order, -number, -direction and is invariant to scaling, translation and rotation. In our stroke-based recognition model, we propose convexity features along with spatial and temporal proximity features to prune the combinatorial search space of possible stroke configurations to form shapes. This reduces the problem of exponential complexity to polynomial one while reducing the error by 24% compared to temporal proximity based criterion. The strokes are then recognized using geometric polygonal features against a neural-net based classifier for 17 classes. The diagramming system is based on stroke-based classifier combination model where an arbitrator makes context aware decisions using suggestions from shape, connector and writing-drawing experts. We achieved an accuracy of 92.7%, 81.4% and 91.5% on the respective experts for a collection of 700,000 online shapes.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"6 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131637536","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 Impact of Ruling Lines on Writer Identification","authors":"Jin Chen, D. Lopresti, E. Kavallieratou","doi":"10.1109/ICFHR.2010.75","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.75","url":null,"abstract":"Paper often includes pre-printed ruling lines to help people write more neatly. This particular example of real- world noise can have a serious impact on applications such as handwriting recognition and writer identification, however. In this work, we investigate the effects of ruling lines on writer ID. We study a method for detecting and removing ruling lines and test its utility for Arabic writer identification through a series of experiments. Our preliminary results show that under realistic assumptions where ruling lines are expected to have different properties across the collection, e.g., thickness, spacing, etc., removing them significantly improves identification performance. We conclude with a discussion of work-in-progress to examine follow up questions raised by our initial investigations.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129706197","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":"International Conference on Frontiers in Handwriting Recognition (ICFHR 2010) - Competitions Overview","authors":"H. E. Abed, V. Märgner, M. Blumenstein","doi":"10.1109/ICFHR.2010.114","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.114","url":null,"abstract":"The great success and high number of participants in pattern recognition related competitions last years show an important improvement of recognition and classification approaches. This success is unconceivable without the availability of huge datasets of real world data. We have invited for proposals for competitions to be held in the framework of the 12th International Conference on Frontiers in Handwriting Recognition (ICFHR2010). These competitions should aim at evaluating the performance of algorithms and methods for a particular task of Handwriting Recognition. Eight different teams composed of more than one group have submitted their proposals. The subjects of these propositions cover the field of research of handwriting recognition from pre-processing over handwritten document analysis to handwriting text/word recognition. These competitions represent an overview of current research topics and frontiers in handwriting document analysis and recognition. Only 5 competitions have received enough participants (we have defined the threshold to 3 systems) to present their evaluation at the ICFHR 2010. This paper presents the 8 competition proposals with lists of competition organizers and lists of participating systems and approaches.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130221540","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}
Javier Galbally, Julian Fierrez, M. Martinez-Diaz, J. Ortega-Garcia, R. Plamondon, C. O’Reilly
{"title":"Kinematical Analysis of Synthetic Dynamic Signatures Using the Sigma-Lognormal Model","authors":"Javier Galbally, Julian Fierrez, M. Martinez-Diaz, J. Ortega-Garcia, R. Plamondon, C. O’Reilly","doi":"10.1109/ICFHR.2010.24","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.24","url":null,"abstract":"The kinematical information present in synthetically generated signatures is analyzed using the Sigma-Lognormal model and compared to the kinematical properties of real samples. Experiments are carried out on totally independent development and test sets and show a high degree of similarity between humanly produced and artificial signatures. One particular flaw is found in the velocity profile of synthetic signatures. Two possible solutions are proposed to improve the synthetic generation method using the Kinematic Theory of rapid human movements.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131228089","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}
A. Chowriappa, R. N. Rodrigues, T. Kesavadas, V. Govindaraju, A. Bisantz
{"title":"Generation of Handwriting by Active Shape Modeling and Global Local Approximation (GLA) Adaptation","authors":"A. Chowriappa, R. N. Rodrigues, T. Kesavadas, V. Govindaraju, A. Bisantz","doi":"10.1109/ICFHR.2010.40","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.40","url":null,"abstract":"The generation of handwriting is a complex task. In order to accommodate for the large variations involved in handwritten words deformable templates need to be used. In this paper we propose a handwriting model, based on Active shape modeling (ASM). In a two-step generation process, a template-based ASM generates characters and a Gaussian mixture regression (GMR) model concatenates the generated characters. For real time generation of cursive handwriting an adaptation of Global local approximation (GLA) methodology is used to fit the generated models.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132122436","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}
G. Fink, Szilárd Vajda, U. Bhattacharya, S. K. Parui, B. Chaudhuri
{"title":"Online Bangla Word Recognition Using Sub-Stroke Level Features and Hidden Markov Models","authors":"G. Fink, Szilárd Vajda, U. Bhattacharya, S. K. Parui, B. Chaudhuri","doi":"10.1109/ICFHR.2010.68","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.68","url":null,"abstract":"For automatic recognition of Bangla script, only a few studies are reported in the literature, which is in contrast to the role of Bangla as one of the world's major scripts. In this paper we present a new approach to online Bangla handwriting recognition and one of the first to consider cursively written words instead of isolated characters. Our method uses a sub-stroke level feature representation of the script and a writing model based on hidden Markov models. As for the latter an appropriate internal structure is crucial, we investigate different approaches to defining model structures for a highly compositional script like Bangla. In experimental evaluations of a writer independent Bangla word recognition task we show that the use of context-dependent sub-word units achieves quite promising results and significantly outperforms alternatively structured models.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123749903","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}
Hanyu Yan, Lianwen Jin, C. Viard-Gaudin, H. Mouchère
{"title":"SCUT-COUCH Textline_NU: An Unconstrained Online Handwritten Chinese Text Lines Dataset","authors":"Hanyu Yan, Lianwen Jin, C. Viard-Gaudin, H. Mouchère","doi":"10.1109/ICFHR.2010.123","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.123","url":null,"abstract":"An unconstrained online handwritten Chinese text lines dataset, SCUT-COUCH Textline_NU, a subset of SCUT-COUCH [1] [2], is built to facilitate the research of unconstrained online Chinese text recognition. Texts for hand copying are sampled from China Daily corpus with a stratified random manner. The current vision of SCUT-COUCH Textline_NU has 8,809 text lines (4,813 lines are collected by touch screen LCD and 3,996 by digital pen) and 159,866 characters in total that are written by more than 157 participants. To demonstrate that the dataset is practical, an over-segmentation, dynamic programming and semantic model based algorithm was presented for segmenting and recognizing the unconstrained online Chinese text lines. In preliminary experiments on the dataset, the proposed algorithm recognition achieves a baseline accuracy of 56.41%.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124360436","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}