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Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Morphology Based Handwritten Line Segmentation using Foreground and Background Information |
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Conference Article |
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2008 |
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International Conference on Frontiers in Handwriting Recognition, |
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241–246 |
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Montreal (Canada) |
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ICFHR |
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DAG @ dag @ RPL2008a |
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1050 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Recognition of Multi-oriented Touching Characters in Graphical Documents |
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Conference Article |
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Year |
2008 |
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Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, |
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16 |
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297–304 |
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ICVGIP ’08 |
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DAG @ dag @ RPL2008c |
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1080 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Seal detection and recognition: An approach for document indexing |
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Conference Article |
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Year |
2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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101–105 |
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Reliable indexing of documents having seal instances can be achieved by recognizing seal information. This paper presents a novel approach for detecting and classifying such multi-oriented seals in these documents. First, Hough Transform based methods are applied to extract the seal regions in documents. Next, isolated text characters within these regions are detected. Rotation and size invariant features and a support vector machine based classifier have been used to recognize these detected text characters. Next, for each pair of character, we encode their relative spatial organization using their distance and angular position with respect to the centre of the seal, and enter this code into a hash table. Given an input seal, we recognize the individual text characters and compute the code for pair-wise character based on the relative spatial organization. The code obtained from the input seal helps to retrieve model hypothesis from the hash table. The seal model to which we get maximum hypothesis is selected for the recognition of the input seal. The methodology is tested to index seal in rotation and size invariant environment and we obtained encouraging results. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG @ dag @ RPL2009b |
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1239 |
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Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Seal Object Detection in Document Images using GHT of Local Component Shapes |
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Conference Article |
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2010 |
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10th ACM Symposium On Applied Computing |
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23–27 |
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Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents. |
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Sierre, Switzerland |
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SAC |
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DAG @ dag @ RPL2010a |
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1291 |
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Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Query Driven Word Retrieval in Graphical Documents |
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Conference Article |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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191–198 |
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In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. |
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Boston; USA |
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978-1-60558-773-8 |
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DAS |
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Call Number |
DAG @ dag @ RPL2010b |
Serial |
1433 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Touching Text Character Localization in Graphical Documents using SIFT |
Type |
Conference Article |
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Year |
2009 |
Publication |
In proceedings 8th IAPR International Workshop on Graphics Recognition |
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Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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La rochelle; July 2009 |
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GREC |
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DAG @ dag @ RPL2009c |
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1445 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Document Seal Detection Using Ght and Character Proximity Graphs |
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Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
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PR |
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44 |
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6 |
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1282-1295 |
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Seal recognition; Graphical symbol spotting; Generalized Hough transform; Multi-oriented character recognition |
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This paper deals with automatic detection of seal (stamp) from documents with cluttered background. Seal detection involves a difficult challenge due to its multi-oriented nature, arbitrary shape, overlapping of its part with signature, noise, etc. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors computed from recognition result of individual connected components (characters). Scale and rotation invariant features are used in a Support Vector Machine (SVM) classifier to recognize multi-scale and multi-oriented text characters. The concept of generalized Hough transform (GHT) is used to detect the seal and a voting scheme is designed for finding possible location of the seal in a document based on the spatial feature descriptor of neighboring component pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal in a document. Experiment is performed in an archive of historical documents of handwritten/printed English text. Experimental results show that the method is robust in locating seal instances of arbitrary shape and orientation in documents, and also efficient in indexing a collection of documents for retrieval purposes. |
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Elsevier |
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Admin @ si @ RPL2011 |
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1820 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Text line extraction in graphical documents using background and foreground |
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Journal Article |
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2012 |
Publication |
International Journal on Document Analysis and Recognition |
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IJDAR |
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15 |
Issue |
3 |
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227-241 |
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0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such 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. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions,
individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in
the document. |
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1433-2833 |
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Admin @ si @ RPL2012b |
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2134 |
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Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Touching Text Character Localization in Graphical Documents using SIFT |
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2010 |
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Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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199-211 |
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Support Vector Machine; Text Component; Graphical Line; Document Image; Scale Invariant Feature Transform |
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Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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Admin @ si @ RPL2010c |
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2408 |
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Partha Pratim Roy; Josep Llados; Umapada Pal |
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Title |
Text/Graphics Separation in Color Maps |
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Conference Article |
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2007 |
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International Conference on Computing: Theory and Applications |
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545–551 |
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Kolkata (India) |
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ICCTA |
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DAG @ dag @ RLP2007a |
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806 |
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