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2014 11th IAPR International Workshop on Document Analysis Systems最新文献

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Iterative Bipartite Graph Edit Distance Approximation 迭代二部图编辑距离逼近
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.16
Kaspar Riesen, Rolf Dornberger, H. Bunke
{"title":"Iterative Bipartite Graph Edit Distance Approximation","authors":"Kaspar Riesen, Rolf Dornberger, H. Bunke","doi":"10.1109/DAS.2014.16","DOIUrl":"https://doi.org/10.1109/DAS.2014.16","url":null,"abstract":"One of the major tasks in many applications in the field of document analysis is the computation of dissimilarities between two or more objects from a given problem domain. Hence, employing graphs as representation formalism evokes the need for powerful, fast and flexible graph based dissimilarity models. Graph edit distance is powerful and applicable to any kind of graphs but suffers from its high computational complexity. Recently, however, a novel framework for graph edit distance approximation has been introduced. While the run time of this novel procedure is very convincing, the precision of the approximated graph distances is dissatisfying in some cases. The present paper introduces a generalized version of the existing approximation framework using an iterative bipartite procedure. With empirical investigations on three real world data sets we show that our extension substantially improves the accuracy of the approximations while the run time is increased only linearly with the number of additional iterations.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117148856","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
Design of Unsupervised Feature Extraction System for On-line Bangla Handwriting Recognition 在线孟加拉文手写识别的无监督特征提取系统设计
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.55
Volkmar Frinken, Nilanjana Bhattacharya, U. Pal
{"title":"Design of Unsupervised Feature Extraction System for On-line Bangla Handwriting Recognition","authors":"Volkmar Frinken, Nilanjana Bhattacharya, U. Pal","doi":"10.1109/DAS.2014.55","DOIUrl":"https://doi.org/10.1109/DAS.2014.55","url":null,"abstract":"Different systems for handwriting recognition use different features to represent the input text. Even after decades of research, no favorable decision on a best-practice exists and many features are carefully hand-crafted. To facilitate the design phase for on-line handwriting systems, in this paper, we propose an unsupervised feature generation approach based on dissimilarity space embedding (DSE) of local neighborhoods around the points along the trajectory. DSE has high capability of discriminative representation and hence beneficial for classification. We compare the approach with a state-of-the-art feature extraction method and demonstrate its superiority.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124810615","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
On-line Handwritten Mathematical Expression Recognition Method Based on Statistical and Semantic Analysis 基于统计和语义分析的在线手写数学表达式识别方法
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.47
Yang Hu, Liangrui Peng, Yejun Tang
{"title":"On-line Handwritten Mathematical Expression Recognition Method Based on Statistical and Semantic Analysis","authors":"Yang Hu, Liangrui Peng, Yejun Tang","doi":"10.1109/DAS.2014.47","DOIUrl":"https://doi.org/10.1109/DAS.2014.47","url":null,"abstract":"Recognition of handwritten mathematical expressions (HMEs) has become a cutting edge research topic recently, as there are increasingly needs for pen-inputting applications. In this paper, we presented a novel framework to analyse HME layout and semantic information. This framework includes three steps, namely symbol segmentation, symbol recognition and semantic relationship analysis. For symbol segmentation, a decomposition on strokes is operated, then dynamic programming is adopted to find the paths corresponding to the best segmentation manner and reduce the stroke searching complexity. For symbol recognition, spatial geometry and directional element features are classified by a Gaussian Mixture Model learnt through Expectation-Maximization algorithm. At last, in the semantic relationship analysis module, a ternary tree is utilized to to store the ranked symbols through calculating the operator priorities. The motivation for our work comes from the apparent difference in writing styles across western and Chinese populations. Our results are reasonable and show promise on the private dataset.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132471941","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
Multi-oriented Text Recognition in Graphical Documents Using HMM 基于HMM的图形文档多方向文本识别
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.27
P. Roy, Sangheeta Roy, U. Pal
{"title":"Multi-oriented Text Recognition in Graphical Documents Using HMM","authors":"P. Roy, Sangheeta Roy, U. Pal","doi":"10.1109/DAS.2014.27","DOIUrl":"https://doi.org/10.1109/DAS.2014.27","url":null,"abstract":"The text lines in graphical documents (e.g., maps, engineering drawings), artistic documents etc., are often annotated in curve lines to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted and recognized. Due to presence of multi-oriented characters in such non-structured layout, word recognition is a challenging task. In this paper, we present an approach towards the recognition of scale and orientation invariant text words in graphical documents using Hidden Markov Models (HMM). First, a line extraction method is applied to segment text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. For recognition of curved text lines, a path of sliding window is estimated and features extracted from the sliding window are fed to the HMM system for recognition. Local gradient histogram (LGH) based frame-wise feature is used in HMM. The experimental results are evaluated on a dataset of graphical words and we have obtained encouraging results.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125380398","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 New One-Class Classification Method Based on Symbolic Representation: Application to Document Classification 一种基于符号表示的单类分类方法:在文档分类中的应用
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.77
Fahimeh Alaei, Nathalie Girard, Sabine Barrat, Jean-Yves Ramel
{"title":"A New One-Class Classification Method Based on Symbolic Representation: Application to Document Classification","authors":"Fahimeh Alaei, Nathalie Girard, Sabine Barrat, Jean-Yves Ramel","doi":"10.1109/DAS.2014.77","DOIUrl":"https://doi.org/10.1109/DAS.2014.77","url":null,"abstract":"Training a system using a small number of instances to obtain accurate recognition/classification is a crucial need in document classification domain. The one-class classification is chosen since only positive samples are available for the training. In this paper, a new one-class classification method based on symbolic representation method is proposed. Initially a set of features is extracted from the training set. A set of intervals valued symbolic feature vector is then used to represent the class. Each interval value (symbolic data) is computed using mean and standard deviation of the corresponding feature values. To evaluate the proposed one-class classification method a dataset composed of 544 document images was used. Experiment results reveal that the proposed one-class classification method works well even when the number of training samples is small (≤10). Moreover, we noted that the proposed one-class classification method is suitable for document classification and provides better result compared to one-class k-nearest neighbor (k-NN) classifier.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125598743","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: 10
Land Map Images Binarization Based on Distance Transform and Adaptive Threshold 基于距离变换和自适应阈值的土地地图图像二值化
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.15
Samit Biswas, Sekhar Mandal, A. Das, B. Chanda
{"title":"Land Map Images Binarization Based on Distance Transform and Adaptive Threshold","authors":"Samit Biswas, Sekhar Mandal, A. Das, B. Chanda","doi":"10.1109/DAS.2014.15","DOIUrl":"https://doi.org/10.1109/DAS.2014.15","url":null,"abstract":"This work presents a binarization technique of map document images. It exploits an amalgam of global and local threshold approaches best suited for binarization of document images with complex background and overlapping objects in the foreground like maps. The proposed approach uses Distance Transform (DT) and Adaptive threshold. Initially a rough estimate of the map background is done using Distance Transform (DT). This is followed by an adaptive threshold operation to extract the foreground. The efficacy and accuracy of the proposed technique are also compared, using ICDAR 2009 -- DIBCO (Document Image Binarization Contest) evaluation parameters, with other algorithms already reported in the literature.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132533868","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
Logical Labeling of Fixed Layout PDF Documents Using Multiple Contexts 使用多个上下文的固定布局PDF文档的逻辑标记
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.54
Xin Tao, Zhi Tang, Canhui Xu, Yongtao Wang
{"title":"Logical Labeling of Fixed Layout PDF Documents Using Multiple Contexts","authors":"Xin Tao, Zhi Tang, Canhui Xu, Yongtao Wang","doi":"10.1109/DAS.2014.54","DOIUrl":"https://doi.org/10.1109/DAS.2014.54","url":null,"abstract":"The task of logical structure recovery is known to be of crucial importance, yet remains unsolved not only for image based document but also for born-digital document system. In this work, the modeling of contextual information based on 2D Conditional Random Fields is proposed to learn page structure for born-digital fixed-layout documents. Heuristic prior knowledge of Portable Document Format (PDF) content and layout are interpreted to construct neighborhood graphs and various pair wise clique templates for the modeling of multiple contexts. By integrating local and contextual observations obtained from PDF attributes, the ambiguities of semantic labels are better resolved. Experimental comparisons for six types of clique templates has demonstrated the benefits of contextual information in logical labeling of 16 finely defined categories.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117302675","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: 11
NIST 2013 Open Handwriting Recognition and Translation (Open HaRT'13) Evaluation NIST 2013开放手写识别和翻译(Open HaRT'13)评估
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.43
Audrey Tong, Mark A. Przybocki, V. Märgner, H. E. Abed
{"title":"NIST 2013 Open Handwriting Recognition and Translation (Open HaRT'13) Evaluation","authors":"Audrey Tong, Mark A. Przybocki, V. Märgner, H. E. Abed","doi":"10.1109/DAS.2014.43","DOIUrl":"https://doi.org/10.1109/DAS.2014.43","url":null,"abstract":"This paper describes the NIST 2013 Open Handwriting Recognition and Translation evaluation (OpenHaRT'13). A short background leading to the start of OpenHaRT is included. The test designs pertaining to the tasks, the data used, the performance measurements, and the protocols are presented. The participants and their submissions are mentioned followed by the evaluation results and some preliminary analyses. The paper concludes with some thoughts toward future evaluations.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130031888","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
Real-Time Document Image Super-Resolution by Fast Matting 快速抠图的实时文档图像超分辨率
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.32
Yun Zheng, Xudong Kang, Shutao Li, Yuan He, Jun Sun
{"title":"Real-Time Document Image Super-Resolution by Fast Matting","authors":"Yun Zheng, Xudong Kang, Shutao Li, Yuan He, Jun Sun","doi":"10.1109/DAS.2014.32","DOIUrl":"https://doi.org/10.1109/DAS.2014.32","url":null,"abstract":"From a single low resolution image, a real-time document image super-resolution algorithm is proposed to obtain high resolution document image with sharp text boundaries. First, a highly efficient document image matting algorithm based on local linear modeling is designed to decompose the input image into text, foreground and background layers, which contain the text edge information, the color information of the foreground and background respectively. Then the text layer is up-sampled with Teager filter to increase the sharpness of the text. For efficiency, the foreground and background layers are simply up-sampled through the bi-cubic interpolation. Finally, these three high resolution layers are composed to obtain the high-resolution image. Experiments on real scanned document images demonstrate the effectiveness of the proposed method in both visual perception and OCR performance.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128693954","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: 9
Fast and Optimal Binary Template Matching Application to Manga Copyright Protection 快速优化二进制模板匹配在漫画版权保护中的应用
2014 11th IAPR International Workshop on Document Analysis Systems Pub Date : 2014-04-07 DOI: 10.1109/DAS.2014.80
Mathieu Delalandre, M. Iwata, K. Kise
{"title":"Fast and Optimal Binary Template Matching Application to Manga Copyright Protection","authors":"Mathieu Delalandre, M. Iwata, K. Kise","doi":"10.1109/DAS.2014.80","DOIUrl":"https://doi.org/10.1109/DAS.2014.80","url":null,"abstract":"Template matching is a technique used in classifying an object by comparing portions of images with another image. Finding a given template in an image is typically performed by scanning the image and evaluating the similarity with the template. When the scanning is concerned with the entire image template matching is optimal. This paper considers a special case of template matching where the templates are binary. Although binary template matching has been studied extensively since the early days of pattern recognition, this technique seems not longer in use in Document Image Analysis (DIA). The major reasons arête time complexity, the no-invariance to scale and rotation and the lack of adaptability of similarity measures. However, different contributions have been investigated during the last years to improve these aspects: robustness and discrimination capability of similarity measures, their characterization, time-processing optimization with hardware support, etc. In this paper, we will review first some of the recent issues about binary template matching. We will present then a system exploiting bitwise operators and parallel processing supporting fast and accurate binary template matching for Manga copyright protection. This system is compared to a FFT-based template matching, and it outperforms both in processing-time and detection accuracy.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124381841","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
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