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2012 International Conference on Frontiers in Handwriting Recognition最新文献

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Semi-customizable Gestural Commands Approach and Its Evaluation 半可定制手势命令方法及其评价
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.267
Peiyu Li, Ney Renau-Ferrer, É. Anquetil, Eric Jamet
{"title":"Semi-customizable Gestural Commands Approach and Its Evaluation","authors":"Peiyu Li, Ney Renau-Ferrer, É. Anquetil, Eric Jamet","doi":"10.1109/ICFHR.2012.267","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.267","url":null,"abstract":"Pen-based interfaces allow users to interact with the help of a stylus and/or fingers. Thanks to a recognition system, users can execute commands by drawing gestures. Because of the complexity of the software, the set of gesture commands can be very large. Consequently, it becomes difficult for the users to remember all the commands. In this paper we introduce \"Semi-customizable gestural commands\". The idea is to take into account the commands usage frequency: to facilitate the memorization of the most used commands we leave users the freedom/liberty to define their associated gestures (by) themselves. The remaining gesture commands will be automatically generated on the base of the defined gestures according to their hierarchical categorization. Several comparative tests demonstrate that this new approach improved the progressive memorization of the gestural commands.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131985607","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}
引用次数: 12
Effective Technique for the Recognition of Writer Independent Off-Line Handwritten Arabic Words 作者自主离线手写阿拉伯语单词识别的有效技术
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.200
S. Abdelazeem, Hany Ahmed
{"title":"Effective Technique for the Recognition of Writer Independent Off-Line Handwritten Arabic Words","authors":"S. Abdelazeem, Hany Ahmed","doi":"10.1109/ICFHR.2012.200","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.200","url":null,"abstract":"In this paper we present a novel segmentation-free Arabic handwriting recognition system based on hidden Markov model (HMM). Two main contributions are introduced: a novel pre-processing method and a new technique for dividing the image into non uniform horizontal segments to extract the features. The proposed system first pre-processes the input image by setting the thickness of the input word to three pixels and fixing the spacing between the different parts of the word. The input image is then divided into constant number of non uniform horizontal segments depending on the distribution of the foreground pixels. A set of robust features representing the foreground pixels is extracted using vertical sliding windows. The proposed system builds character HMM models and learns word HMM models using embedded training data. The performance of the proposed system is very promising compared with other Arabic handwriting recognition systems available in the literature.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131236715","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}
引用次数: 5
A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection 一种从粗到精的大规模历史文献手写体词识别方法
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.151
Jon Almazán, D. F. Mota, A. Fornés, J. Lladós, Ernest Valveny
{"title":"A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection","authors":"Jon Almazán, D. F. Mota, A. Fornés, J. Lladós, Ernest Valveny","doi":"10.1109/ICFHR.2012.151","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.151","url":null,"abstract":"In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134015998","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}
引用次数: 18
HMM-based Offline Arabic Handwriting Recognition: Using New Feature Extraction and Lexicon Ranking Techniques 基于hmm的离线阿拉伯手写识别:使用新的特征提取和词典排序技术
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.214
Hesham M. Eraqi, S. Abdelazeem
{"title":"HMM-based Offline Arabic Handwriting Recognition: Using New Feature Extraction and Lexicon Ranking Techniques","authors":"Hesham M. Eraqi, S. Abdelazeem","doi":"10.1109/ICFHR.2012.214","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.214","url":null,"abstract":"In this paper, a new offline Arabic handwriting recognition system is presented. The Douglas-Peucker algorithm is applied on the skeletonized parts of the offline images to convert it into piecewise linear curves that are used for efficient detection of diacritics, noise segments, and the baseline. A hidden Markov model (HMM)-based system is used with features extracted from the image before and after removing the diacritics. A reliable method of lexicon ranking and reduction based on the information of the image's diacritics, number of piece of Arabic words (PAWs), and dimensions information is used. The proposed system has been tested using the IFN/ENIT database and has achieved promising recognition rates.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133374120","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}
引用次数: 8
Arabic handwritten word spotting using language models 使用语言模型识别阿拉伯语手写单词
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.183
Muna Khayyat, L. Lam, C. Suen
{"title":"Arabic handwritten word spotting using language models","authors":"Muna Khayyat, L. Lam, C. Suen","doi":"10.1109/ICFHR.2012.183","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.183","url":null,"abstract":"With the ever-increasing amounts of published materials being made available, developing efficient means of locating target items has become a subject of significant interest. Among the approaches adopted for this purpose is word spotting, which enables the identification of documents through the use of pertinent keywords. This paper reports on an effective method of word spotting for Arabic handwritten documents that takes into consideration the nature of Arabic handwriting. Parts of Arabic Words (PAWs) form the basic components of this search process, and a hierarchical classifier (consisting of a set of classifiers each trained on a different part of the input pattern) is implemented. For the first time in Arabic word spotting, language models are incorporated into the process of reconstructing words from PAWs. Details of the method and promising experimental results are also presented.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130806946","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}
引用次数: 18
Segmentation and Word Spotting Methods for Printed and Handwritten Arabic Texts: A Comparative Study 阿拉伯语印刷与手写文本的分词与词识别方法:比较研究
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.266
M. Kchaou, S. Kanoun, J. Ogier
{"title":"Segmentation and Word Spotting Methods for Printed and Handwritten Arabic Texts: A Comparative Study","authors":"M. Kchaou, S. Kanoun, J. Ogier","doi":"10.1109/ICFHR.2012.266","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.266","url":null,"abstract":"This paper presents a comparative study for word spotting techniques according to holistic approach. So, the current work consists in experimenting word image segmentation, characterization and matching to show the most reliable techniques. The experimental process is done in the same printed and handwritten Arabic dataset. Our aim is to realize an effective system of information retrieval.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130539198","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}
引用次数: 15
Statistical Hypothesis Testing for Handwritten Word Segmentation Algorithms 手写分词算法的统计假设检验
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.272
Mehdi Haji, K. Sahoo, T. D. Bui, C. Suen, Dominique Ponson
{"title":"Statistical Hypothesis Testing for Handwritten Word Segmentation Algorithms","authors":"Mehdi Haji, K. Sahoo, T. D. Bui, C. Suen, Dominique Ponson","doi":"10.1109/ICFHR.2012.272","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.272","url":null,"abstract":"We present a statistical hypothesis testing method for handwritten word segmentation algorithms. Our proposed method can be used along with any word segmentation algorithm in order to detect over-segmented or under-segmented errors or to adapt the word segmentation algorithm to new data in an unsupervised manner. The main idea behind the proposed approach is to learn the geometrical distribution of words within a sentence using a Markov chain or a Hidden Markov Model (HMM). In the former, we assume all the necessary information is observable, where in the latter, we assume the minimum observable variables are the bounding boxes of the words, and the hidden variables are the part of speech information. Our experimental results on a benchmark database show that not only we can achieve a lower over-segmentation and under-segmentation error rate, but also a higher correct segmentation rate as a result of the proposed hypothesis testing.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115114837","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}
引用次数: 8
Mode Detection in Online Handwritten Documents Using BLSTM Neural Networks 基于BLSTM神经网络的在线手写文档模式检测
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.232
Emanuel Indermühle, Volkmar Frinken, H. Bunke
{"title":"Mode Detection in Online Handwritten Documents Using BLSTM Neural Networks","authors":"Emanuel Indermühle, Volkmar Frinken, H. Bunke","doi":"10.1109/ICFHR.2012.232","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.232","url":null,"abstract":"Mode detection in online handwritten documents refers to the process of distinguishing different types of contents, such as text, formulas, diagrams, or tables, one from another. In this paper a new approach to mode detection is proposed that uses bidirectional long-short term memory (BLSTM) neural networks. The BLSTM neural network is a novel type of recursive neural network that has been successfully applied in speech and handwriting recognition. In this paper we show that it has the potential to significantly outperform traditional methods for mode detection, which are usually based on stroke classification. As a further advantage over previous approaches, the proposed system is trainable and does not rely on user-defined heuristics. Moreover, it can be easily adapted to new or additional types of modes by just providing the system with new training data.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"583 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120942259","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}
引用次数: 41
A Hybrid for Line Segmentation in Handwritten Documents 一种用于手写文档线段分割的混合算法
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.156
Hande Adiguzel, Emre Sahin, P. D. Sahin
{"title":"A Hybrid for Line Segmentation in Handwritten Documents","authors":"Hande Adiguzel, Emre Sahin, P. D. Sahin","doi":"10.1109/ICFHR.2012.156","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.156","url":null,"abstract":"This paper presents an approach for text line segmentation which combines connected component based and projection based information to take advantage of aspects of both methods. The proposed system finds baselines of each connected component. Lines are detected by grouping baselines of connected components belonging to each line by projection information. Components are assigned to lines according to different distance metrics with respect to their size. This study is one of the rare studies that apply line segmentation to Ottoman documents. Further, it proposes a new method, Fourier curve fitting, to detect the peaks in a projection profile. The algorithm is demonstrated on different printed and handwritten Ottoman datasets. Results show that the method manages to segment lines both from printed and handwritten documents under different writing conditions at least with 92% accuracy.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"89 3 Pt 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122507850","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}
引用次数: 15
Competitive Hybrid Exploration for Off-Line Sketches Structure Recognition 离线草图结构识别的竞争混合探索
2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.195
Achraf Ghorbel, Aurélie Lemaitre, É. Anquetil
{"title":"Competitive Hybrid Exploration for Off-Line Sketches Structure Recognition","authors":"Achraf Ghorbel, Aurélie Lemaitre, É. Anquetil","doi":"10.1109/ICFHR.2012.195","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.195","url":null,"abstract":"We work on new strategies of exploration for interpretation of off-line sketches. A first approach (call IMISketch) was based on a competitive breadth-first exploration of the analysis tree allowing to evaluate simultaneously several possible hypotheses of recognition in a dynamic local context of document. A great advantage of this strategy is to be able to solicit the user during the decision process to avoid error accumulation in the analysis step. IMISketch strategy is very interesting but it can lead combinatory problems when addressing complex sketches. In this paper, we propose a new hybrid strategy for exploration. The recognition process alternates between a breadth-first and depth-first exploration. The strategy is totally driven by the grammatical description of the document. The paper demonstrates the interest of this new hybrid strategy method on handwritten 2D architectural floor plans containing walls, opening and furnitures.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128658937","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}
引用次数: 13
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