Segmentation of heterogeneous document images : an ... - Tel

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of text lines using a criterion that depends on the geometric appearances and indentations of text lines in a paragraph. 1.5 Our datasets One of the datasets used for testing and training in this work is a selection of document images from a huge corpus, that were provided for the purpose of this project. The original corpus contains historical handwritten manuscripts and old printed forms, documents and advertisements, mostly written in French language. We have chosen a subset of 100 documents from this corpus that represents the original set. Figure 1.5 shows some samples of our own dataset. tel-00912566, version 1 - 2 Dec 2013 In addition, we gathered 61 documents used as part of the dataset in IC- DAR2009 [6] page segmentation competition and 100 documents from the dataset used in ICDAR2011 [4] historical document layout analysis competition, to be able to compare our results with the state-of-the-art methods. Some samples from these datasets are shown in figure 1.6. For each document a ground truth file is available. The ground truth file contains the true structure of text regions and text lines for each document. By far ground truth data are the most important part of the work for the purpose of both training and testing various parts of the system. They are usually in text format and contain coordinates of objects in a hierarchical structure. For text and graphics separation we only need the original document image and the location of true text regions. Every component that does not belong to a text region is considered a non-text element. A collection of textual and non-textual components are used for the purpose of training. In text region detection, we divide every document into sites with predefined heights and widths. By knowing whether a site is located on the text or non-text region of the ground truth, we can easily generate our true labels for the purpose of training our region detector. For text line and paragraph detection we consider the geometry appearance and relative position of text lines defined in the ground truth structure. In the first stages of the project, we had no ground truth date for any of the datasets. So we developed a software to generate our own true data. Figure 1.7 shows a screen shot of our developed software. After opening an image, the software renders a scene of all connected components extracted from the image. The user can group several connected components as a text line. With the same strategy the user can group several text lines as a paragraph. In case a large connected component (a table or a frame of advertisement) occults other smaller components, the user has the option to deactivate that particular component. Finally, the application generates an XML file for each document with the correct structure to be used as a ground truth. Figure 1.8 shows part of an XML file created by our software. Later, we got access to ground truth data for ICDAR2009 dataset. The new ground truth data are also provided in XML format but the nodes and elements of the new XML documents are different from ours. Because the dataset and ground truth data belong to Prima group at University of Salford, 8
tel-00912566, version 1 - 2 Dec 2013 Figure 1.5: Some sample documents from our own corpus. 9
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Page 3 and 4: Resumé La segmentation de page est
Page 5 and 6: Acknowledgements This work would no
Page 7 and 8: 4.3.2 Text components . . . . . . .
Page 9 and 10: 3.6 Two documents that have obtaine
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Page 23 and 24: Chapter 2 Related work tel-00912566
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(a) Document (b) Filled text compon
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f = [y c = 0] × [y tl = 0] f = [y
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(a) Ground-truth (b) y c = 0 tel-00
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∂l λ = ∑ ( ∑y∈Y f k (y s ,
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incorrect [100]. Several sufficient
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Table 4.3: TION COUNT WEIGHTED SUCC
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Chapter 5 Text line detection tel-0
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Having specified the model, a verti
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• The fifth step is to remove ext
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text lines can be divided into two
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the two children. The root node rep
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leaves of the tree which contain on
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currently working on some of these
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• fn (false negative) is the numb
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2 ∗ RA ∗ DR F − Measure = RA
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• ”-tn”: This option uses the
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[12] T. M. Breuel. Two geometric al
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[39] B. Gatos, A. Antonacopoulos, a
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[64] K. P. Murphy, Y. Weiss, and M.
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[91] M. Stamp. A revealing introduc
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Index tel-00912566, version 1 - 2 D
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Segmentation of heterogeneous document images : an ... - Tel

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