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2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)最新文献

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Inkball Models as Features for Handwriting Recognition 墨球模型作为手写识别的特征
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0030
N. Howe, Andreas Fischer, Baptiste Wicht
{"title":"Inkball Models as Features for Handwriting Recognition","authors":"N. Howe, Andreas Fischer, Baptiste Wicht","doi":"10.1109/ICFHR.2016.0030","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0030","url":null,"abstract":"Inkball models provide a tool for matching and comparison of spatially structured markings such as handwritten characters and words. Hidden Markov models offer a framework for decoding a stream of text in terms of the most likely sequence of causal states. Prior work with HMM has relied on observation of features that are correlated with underlying characters, without modeling them directly. This paper proposes to use the results of inkball-based character matching as a feature set input directly to the HMM. Experiments indicate that this technique outperforms other tested methods at handwritten word recognition on a common benchmark when applied without normalization or text deslanting.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208108","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: 3
Beyond the Ground Truth: Alternative Quality Measures of Document Binarizations 超越基本事实:文件二值化的可选质量度量
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0097
Arie Shaus, B. Sober, Eli Turkel, E. Piasetzky
{"title":"Beyond the Ground Truth: Alternative Quality Measures of Document Binarizations","authors":"Arie Shaus, B. Sober, Eli Turkel, E. Piasetzky","doi":"10.1109/ICFHR.2016.0097","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0097","url":null,"abstract":"This article discusses the quality assessment of binary images. The customary, ground truth based methodology, used in the literature is shown to be problematic due to its subjective nature. Several previously suggested alternatives are surveyed and are also found to be inadequate in certain scenarios. A new approach, quantifying the adherence of a binarization to its document image is proposed and tested using six different measures of accuracy. The measures are evaluated experimentally based on datasets from DIBCO and H-DIBCO competitions, with respect to different kinds of binarization degradations.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124420704","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: 4
Convolutional Multi-directional Recurrent Network for Offline Handwritten Text Recognition 面向离线手写文本识别的卷积多向递归网络
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0054
Zenghui Sun, Lianwen Jin, Zecheng Xie, Ziyong Feng, Shuye Zhang
{"title":"Convolutional Multi-directional Recurrent Network for Offline Handwritten Text Recognition","authors":"Zenghui Sun, Lianwen Jin, Zecheng Xie, Ziyong Feng, Shuye Zhang","doi":"10.1109/ICFHR.2016.0054","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0054","url":null,"abstract":"In this paper, we propose a new network architecture called Convolutional Multi-directional Recurrent Network (CDRN) for offline handwritten text recognition. The conventional recurrent neural network model obtains the local context from limited directions, whereas we build up the multi-directional long short-term memory (MDirLSTM) module to abstract contextual information in various directions. Moreover, we develop a shortcut connection strategy in our proposed architecture for faster yet better convergence. In cooperation with the aforementioned methods, the proposed architecture also benefits from the following properties: (1) it obtains informative features of the input directly without involving hand-crafted features and segmentation, and (2) it is an end-to-end trainable model whose components are trained conjointly. We evaluate the performance of the proposed method on two databases: IAM words and IRONOFF. Our experimental results demonstrate a significant increase in recognition performance using MDirLSTM and shortcut connections, which suggests the effectiveness of these two proposed methods.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130425119","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: 25
Cascading Training for Relaxation CNN on Handwritten Character Recognition 放松CNN在手写字符识别上的级联训练
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0041
Li Chen, Song Wang, Wei-liang Fan, Jun Sun, S. Naoi
{"title":"Cascading Training for Relaxation CNN on Handwritten Character Recognition","authors":"Li Chen, Song Wang, Wei-liang Fan, Jun Sun, S. Naoi","doi":"10.1109/ICFHR.2016.0041","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0041","url":null,"abstract":"With the development of deep learning, many difficult recognition problems can be solved by deep learning models. For handwritten character recognition, the CNN is used the most. In order to improve the performance of CNN, many new models have been proposed and in which the relaxation CNN [35] is widely used. The relaxation CNN has more complicated structure than CNN while the recognition time is the same with which. However, the training of relaxation CNN needs much more time than CNN. In this paper, we propose the cascading training for relaxation CNN. Our method can train a relaxation CNN of better performance while using almost the same training time with normal CNN. The experimental results proved that the relaxation CNN trained by cascading training is able to achieve the state-of-the-art performance on handwritten Chinese character recognition.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129010095","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: 3
Online Handwritten Mathematical Expressions Recognition by Merging Multiple 1D Interpretations 合并多个一维解释的在线手写数学表达式识别
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0045
Ting Zhang, H. Mouchère, C. Viard-Gaudin
{"title":"Online Handwritten Mathematical Expressions Recognition by Merging Multiple 1D Interpretations","authors":"Ting Zhang, H. Mouchère, C. Viard-Gaudin","doi":"10.1109/ICFHR.2016.0045","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0045","url":null,"abstract":"In this work, we propose to recognize handwritten mathematical expressions by merging multiple 1D sequences of labels produced by a sequence labeler. The proposed solution aims at rebuilding a 2D expression from several 1D labeled paths. An online math expression is a sequence of strokes which is later used to build a graph considering both temporal and spatial orders among these strokes. In this graph, node corresponds to stroke and edge denotes the relationship between a pair of strokes. Next, we select 1D paths from the built graph with the expectation that these paths could catch all the strokes and the relationships between pairs of strokes. As an advanced and strong sequence classifier, BLSTM networks are adopted to label the selected 1D paths. We set different weights to these 1D labeled paths and then merge them to rebuild a label graph. After that, an additional post-process will be performed to complete the edges automatically. We test the proposed solution and compare the results to the state of art in online math expression recognition domain.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115898724","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: 7
MST-based Visual Parsing of Online Handwritten Mathematical Expressions 基于mst的在线手写数学表达式可视化解析
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0070
Lei Hu, R. Zanibbi
{"title":"MST-based Visual Parsing of Online Handwritten Mathematical Expressions","authors":"Lei Hu, R. Zanibbi","doi":"10.1109/ICFHR.2016.0070","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0070","url":null,"abstract":"We develop a Maximum Spanning Tree (MST) based parser using Edmonds' algorithm, which extracts an MST from a directed Line-of-Sight graph in two passes. First, symbols are segmented by grouping input strokes, and then symbols and symbol pair spatial relationships are labeled. The time complexity of our MST-based parsing is lower than the time complexity of CYK parsing with 2-D Context-Free grammars. Also, our MST-based parser obtains higher formula structure and expression rates than published techniques using CYK parsing when starting from valid symbols. This parsing technique could be extended to include n-grams or other language constraints, and might be used for other notations.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133552755","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: 21
DIVA-HisDB: A Precisely Annotated Large Dataset of Challenging Medieval Manuscripts DIVA-HisDB:一个具有挑战性的中世纪手稿的精确注释大数据集
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0093
Fotini Simistira, Mathias Seuret, Nicole Eichenberger, A. Garz, M. Liwicki, R. Ingold
{"title":"DIVA-HisDB: A Precisely Annotated Large Dataset of Challenging Medieval Manuscripts","authors":"Fotini Simistira, Mathias Seuret, Nicole Eichenberger, A. Garz, M. Liwicki, R. Ingold","doi":"10.1109/ICFHR.2016.0093","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0093","url":null,"abstract":"This paper introduces a publicly available historical manuscript database DIVA-HisDB for the evaluation of several Document Image Analysis (DIA) tasks. The database consists of 150 annotated pages of three different medieval manuscripts with challenging layouts. Furthermore, we provide a layout analysis ground-truth which has been iterated on, reviewed, and refined by an expert in medieval studies. DIVA-HisDB and the ground truth can be used for training and evaluating DIA tasks, such as layout analysis, text line segmentation, binarization and writer identification. Layout analysis results of several representative baseline technologies are also presented in order to help researchers evaluate their methods and advance the frontiers of complex historical manuscripts analysis. An optimized state-of-the-art Convolutional Auto-Encoder (CAE) performs with around 95% accuracy, demonstrating that for this challenging layout there is much room for improvement. Finally, we show that existing text line segmentation methods fail due to interlinear and marginal text elements.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132617450","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: 74
Zoning Aggregated Hypercolumns for Keyword Spotting Zoning用于关键字定位的聚合超列
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0061
Giorgos Sfikas, George Retsinas, B. Gatos
{"title":"Zoning Aggregated Hypercolumns for Keyword Spotting","authors":"Giorgos Sfikas, George Retsinas, B. Gatos","doi":"10.1109/ICFHR.2016.0061","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0061","url":null,"abstract":"In this paper we present a novel descriptor and method for segmentation-based keyword spotting. We introduce Zoning-Aggregated Hypercolumn features as pixel-level cues for document images. Motivated by recent research in machine vision, we use an appropriately pretrained convolutional network as a feature extraction tool. The resulting local cues are subsequently aggregated to form word-level fixed-length descriptors. Encoding is computationally inexpensive and does not require learning a separate feature generative model, in contrast to other widely used encoding methods (such as Fisher Vectors). Keyword spotting trials on machine-printed and handwritten documents show that the proposed model gives very competitive results.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114433860","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: 23
Fusion of Explicit Segmentation Based System and Segmentation-Free Based System for On-Line Arabic Handwritten Word Recognition 基于显式分词和无分词的在线阿拉伯手写体词识别系统融合
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0081
Hanen Khlif, S. Prum, Yousri Kessentini, S. Kanoun, J. Ogier
{"title":"Fusion of Explicit Segmentation Based System and Segmentation-Free Based System for On-Line Arabic Handwritten Word Recognition","authors":"Hanen Khlif, S. Prum, Yousri Kessentini, S. Kanoun, J. Ogier","doi":"10.1109/ICFHR.2016.0081","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0081","url":null,"abstract":"The complexity and viariability of the Arabic handwriting makes difficult the implementation of an efficient recognition system through the use of a unique recognition engine. In this paper, two handwriting word recognition systems are combined in order to take advantage of their complementarities. The first one is a segmentation free based system that uses the generative classifier HMM. The second system is discriminative based. Relying on analytical approach, it proceeds with explicit segmentation of words into graphemes. Different combination strategies are compared including sum, product, Borda count and Dempster-Shafer rules. The experimental results conducted on ADAB database demonstrate a significant improvement of recognition accuracy of 5% compared to the segmentation free based system and 9% compared to the analytical based system.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124563785","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: 4
On the Benefits of Convolutional Neural Network Combinations in Offline Handwriting Recognition 论卷积神经网络组合在离线手写识别中的应用
2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) Pub Date : 2016-10-01 DOI: 10.1109/ICFHR.2016.0046
Dewi Suryani, P. Doetsch, H. Ney
{"title":"On the Benefits of Convolutional Neural Network Combinations in Offline Handwriting Recognition","authors":"Dewi Suryani, P. Doetsch, H. Ney","doi":"10.1109/ICFHR.2016.0046","DOIUrl":"https://doi.org/10.1109/ICFHR.2016.0046","url":null,"abstract":"In this paper, we elaborate the advantages of combining two neural network methodologies, convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent neural networks, with the framework of hybrid hidden Markov models (HMM) for recognizing offline handwriting text. CNNs employ shift-invariant filters to generate discriminative features within neural networks. We show that CNNs are powerful tools to extract general purpose features that even work well for unknown classes. We evaluate our system on a Chinese handwritten text database and provide a GPU-based implementation that can be used to reproduce the experiments. All experiments were conducted with RWTH OCR, an open-source system developed at our institute.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115820219","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: 49
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