2010 12th International Conference on Frontiers in Handwriting Recognition最新文献

{"title":"Incremental MQDF Learning for Writer Adaptive Handwriting Recognition","authors":"Kai Ding, Lianwen Jin","doi":"10.1109/ICFHR.2010.92","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.92","url":null,"abstract":"Writer adaptation has been proved to be an effective approach to improve the recognition performance of the writer-independent recognizer for a particular writer. In this paper, we propose a writer adaptive handwriting recognition approach by incremental learning the Modified Quadratic Discriminant Function (MQDF) classifier. We derived the solution of Incremental MQDF (IMQDF) and then present a Discriminative IMQDF (DIMQDF) by deriving the solution of IMQDF in the updated discriminative feature space. Based on IMQDF or DIMQDF, the writer adaptation is finally performed by updating the MQDF recognizer adaptively. The experimental results for recognizing handwriting Chinese characters indicate that the proposed IMQDF and DIQMDF approaches can reduce as much as 52.71% and 45.38% error rate respectively on the writer-dependent dataset while only have less than 0.18% accuracy loss on the writer-independent dataset. In other words, the proposed IMQDF and DIMQDF based writer adaptation approaches can significantly increase the recognition accuracy on writer-dependent dataset while only have limited negative influence for general writer.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"198 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":"130317235","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":"Reviewing Performance Metrics for Handwriting Recognition: Must-Rejects and Recognition Graph Scores","authors":"M. Schambach","doi":"10.1109/ICFHR.2010.78","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.78","url":null,"abstract":"The performance of handwriting recognition systems is typically measured in terms of “recognition rate”. Many academic competitions work this way. However, additional external requirements may shift the view of recognition quality: Processing time and acceptable error rate may be limited, lexica may be missing, but are needed to unambiguously define result correctness. These aspects will be discussed in detail, and appropriate metrics will be proposed. A single-valued combination of these metrics may then be defined for specific application areas. It can be used in order to choose between recognition approaches or systems, and to optimize system parameters automatically.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"4 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":"130514271","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":"ICFHR 2010 - Arabic Handwriting Recognition Competition","authors":"V. Märgner, H. E. Abed","doi":"10.1109/ICDAR.2011.287","DOIUrl":"https://doi.org/10.1109/ICDAR.2011.287","url":null,"abstract":"This paper describes the Arabic handwriting recognition competition held at International Conference on Frontiers in Handwriting Recognition (ICFHR 2010) in Kolkata, India. This fourth competition (the first was at ICDAR 2005 in Seoul, South Korea, the second at ICDAR 2007 in Curitiba, Brazil and the third at ICDAR 2009 in Barcelona, Spain) again used the IfN/ENIT-database with Arabic handwritten Tunisian town names. Today, more than 100 research groups from universities, research centers, and industry are working with this database worldwide. This year, 4 groups with 6 systems participated at the competition. The systems were tested on known data and on two data sets which were unknown to the participants. The systems were compared based on the most important characteristic: the recognition rate. Additionally, the relative speed of the different systems was compared. A short description of the participating groups, their systems, and the results achieved are finally presented.","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":"116254034","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":"Fast Density Estimation for Approximated k Nearest Neighbor Classification","authors":"Takao Kobayashi, I. Shimizu","doi":"10.1109/ICFHR.2010.60","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.60","url":null,"abstract":"We propose a method for fast density estimation of samples, which makes it possible to significantly accelerate classification based on the k nearest neighbor (kNN) method. Our main premise is that many trials of a rough estimation of probability density function are conducted, and they are integrated by Bayes’ theorem. The experimental results indicated that the classification time used in our method was at least 30 times faster than that of kNN.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"44 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":"127918469","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":"Fuzzy Segmentation and Graphemes Modeling for Online Arabic Handwriting Recognition","authors":"H. Boubaker, A. Chaabouni, M. Kherallah, A. Alimi, H. E. Abed","doi":"10.1109/ICFHR.2010.113","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.113","url":null,"abstract":"In this paper we present a new modeling approach for online Arabic handwriting which is based on fuzzy graphemes segmentation. In the literature, the result of the graphemes segmentation of a cursive writing not often reaches its optimum. This fact is due to the crisp aspect of the segmentation decision. In order to overcome this problem, we propose to introduce a fuzzy effect in this segmentation decision by overlapping the segmented graphemes in proportion to the confidence degrees associated with the detection of the particular points that separate them. The fuzzified boundary shapes of the extracted fuzzy graphemes are then modeled taking into account the coefficient of fuzzy membership of their points. The obtained results by using the ADAB database show an improvement of the recognition rate given by the fuzzy segmentation approach compared to the crisp one.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"84 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":"129615985","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":"Handwritten Mail Classification Experiments with the Rimes Database","authors":"Christopher Kermorvant, J. Louradour","doi":"10.1109/ICFHR.2010.45","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.45","url":null,"abstract":"In this paper, we consider the task of automatic handwritten mail classification and we investigate the relation between the transcription rate and the classification rate. Several configurations of a multi-word handwriting recognizer using different language models are tested and their word recognition rates on the documents to be classified are reported. For the document classification task, we have investigated three different classifiers (KNN, SVM, AdaBoost). All the experiments were conducted on the public database Rimes.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"119 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":"130186580","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":"Automatic Annotation for Handwritten Historical Documents Using Markov Models","authors":"Ines Ben Messaoud, H. E. Abed","doi":"10.1109/ICFHR.2010.66","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.66","url":null,"abstract":"This paper presents a system for automatic annotation of handwritten historical documents based on Markov models. The proposed system first extracts XML schema which describes a specific domain and than a Mapping algorithm is used for the generation of the new XML schemes. Mapping algorithm has as inputs two schemes reference schema and a specific schema. XML schemes are generated using Markov models, this model is used to calculate the Mapping efficiency. In the first model the Mapping increased according to the common number of nodes between the entries XML schemes. Mapping is pertinent when the common nodes number is over $0.5%$ of Markov model states. In the second model the Mapping changes randomly according to the in common number of nodes between $0.05$ and $0.4$.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"81 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":"134075079","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 A2iA-Telecom ParisTech-UOB System for the ICDAR 2009 Handwriting Recognition Competition","authors":"Christopher Kermorvant, F. Menasri, Anne-Laure Bianne-Bernard, Ramy Al-Hajj Mohamad, C. Mokbel, Laurence Likforman-Sulem","doi":"10.1109/ICFHR.2010.46","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.46","url":null,"abstract":"This article describes the isolated word recognizer presented by the authors to the ICDAR 2009 French handwriting recognition competition. The system is a combination of three isolated word recognizers based on different features and models. A novel n-best combination method is proposed and compared to standard combination methods. New results on the ICDAR 2009 test database are reported.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"466 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":"124261165","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":"Detecting Text Areas and Decorative Elements in Ancient Manuscripts","authors":"A. Garz, Markus Diem, Robert Sablatnig","doi":"10.1109/ICFHR.2010.35","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.35","url":null,"abstract":"An approach for the detection of decorative elements – such as initials and headlines – and text regions, focused on ancient manuscripts, is presented. Due to their age, ancient manuscripts suffer from degradation and staining as well as ink is faded-out over the time. Identifying decorative elements and text regions allows indexing a manuscript and serves as input for Optical Character Recognition (OCR) as it localizes regions of interest within document pages. We propose a robust method inspired by state-of-the-art object recognition methodologies. Scale Invariant Feature Transform (SIFT) descriptors are chosen to detect the regions of interest, and the scale of the interest points is used for localization. The classification is based on the fact that local properties of the decorative elements are different to those of regular text. The results show that the method is able to locate regular text in ancient manuscripts. The detection rate of decorative elements is not as high as for regular text but already yields to promising results.","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":"130879700","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":"Neuromuscular Studies of Handwriting Generation and Representation","authors":"R. Plamondon","doi":"10.1109/ICFHR.2010.129","DOIUrl":"https://doi.org/10.1109/ICFHR.2010.129","url":null,"abstract":"Many models have been proposed over the years to study human movements in general and handwriting in particular: models relying on neural networks, dynamics models, psychophysical models, kinematic models and models exploiting minimization principles. Among the models that can be used to provide analytical representations of a pen stroke, the Kinematic Theory of rapid human movements and its delta-lognormal model has often served as a guide in the design of pattern recognition systems relying on the exploitation of the fine neuromotricity, like on-line handwriting recognition, signature verification as well as in the design of intelligent systems involving in a way or another, the global processing of human movements. Among other things, this invited lecture aims at elaborating a theoretical background for many handwriting applications as well as providing some basic knowledge that could be integrated or taking care of in the development of automatic pattern recognition systems. More specifically, we will overview the basic neuromotor properties of single strokes and explain how they can be superimposed vectorially to generate complex pen tip trajectories. Doing so, we will report on various projects conducted by our team and our collaborators. First, we will present a brief comparative survey of the different models in the field and focus on the family of models involving lognormal functions. Then, from a practical perspective, we will describe two new parameter extraction algorithms suitable for the reverse engineering of individual strokes as well as of complex handwriting signals. We will show how the resultingrepresentation could be employed to characterize signers and writers and how the corresponding feature sets could be exploited to study the effects of various factors, like aging and health problems, on handwriting variability. We will also describe some methodologies to generate automatically huge on-line handwriting databases for either writer dependent or writer independent applications as well as for the production of synthetic signature databases. From a theoretical perspective, we will explain how, using an original psychophysical set up, we have been able to validate the basic hypothesis of the Kinematic Theory and to test its most distinctive predictions. We will complete this survey by explaining how the Kinematic Theory could be utilized to improve electromyographic and electroencephalographic signal processing, opening a window on novel potential applications for on-line handwriting processing, particularly in biomedical engineering and in some fields of the neurosciences.","PeriodicalId":335044,"journal":{"name":"2010 12th International Conference on Frontiers in Handwriting Recognition","volume":"77 2 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":"130796577","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}