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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5659
Title: Document seal detection using GHT and character proximity graphs
Authors: Pratim Roy, Partha
Pal U.
Lladós J.
Published in: Pattern Recognition
Abstract: 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 Experiment is performed in an archive of historical documents of handwritten/printed English text.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. © 2010 Elsevier Ltd. All rights reserved.
Citation: Pattern Recognition (2011), 44(6): 1282-1295
URI: https://doi.org/10.1016/j.patcog.2010.12.004
http://repository.iitr.ac.in/handle/123456789/5659
Issue Date: 2011
Keywords: Generalized Hough transform
Graphical symbol spotting
Multi-oriented character recognition
Seal recognition
ISSN: 313203
Author Scopus IDs: 56880478500
57200742116
6603062543
Author Affiliations: Roy, P.P., Computer Vision Centre, Universitat Autonoma de Barcelona, Spain
Pal, U., CVPR Unit, Indian Statistical Institute, Kolkata, India
Lladós, J., Computer Vision Centre, Universitat Autonoma de Barcelona, Spain
Funding Details: In this paper, we have presented a seal detection approach based on spatial arrangement of seal content. A query seal is translated into a set of spatial feature vector using its text character information. These features are used later to locate a seal of similar content in documents. We have used a multi-oriented and multi-scale text character recognition method to generate high level local feature to take care of complex multi-oriented seal information. The recognition result of these character components within seal region is used to generate local spatial information to classify and detect the seal. Relative positional information of text string characters are used for this purpose and hypothesis were generated based on that. The existing systems of seal detection approach consider the seal as a whole object. Use of rotation invariant features [24] to recognize whole seal may not work properly for the seals which are having similar boundary frames, frequent missing of text characters or inclusion of background text characters. The approaches [38] based on seal frame detection cannot recognize the seal type in the document. Also, color-based approaches [35] will not work for degraded binary images. Our approach of seal detection based on GHT of local text characters overcome such problems efficiently. Moreover, our approach can detect the seal even if all the characters from the seal are not extracted. We tested our method in a database of multi-oriented seal documents containing noise, occlusion and overlapping. In retrieval of document image from database, all components of a document pass through the recognition process and hence it is time consuming. So, the improvement of the performance in terms of time could be achieved if a pre-processing method (run-length smoothing) is applied to remove non-seal information from the document. Also the use of boundary-shape information (circular, rectangular, etc.) of seal may improve it further. Partha Pratim Roy has obtained Ph.D. in 2010 from Universitat Autònoma de Barcelona, Spain. He received his Bachelor of Technology degree in Computer Science in 2002 from Kalyani University in India. From 2003 to 2005, he was working as an Assistant System Engineer in Tata Consultancy Services. He obtained his MS in Computer Vision and Image Processing in 2007 from Universitat Autònoma de Barcelona. His research work focuses on the analysis of text/symbol present in graphical documents. It includes understanding of text graphics separation from graphical documents and recognition of text/graphics in multi-scale and multi-orientation environment. Umapada Pal received his Ph.D. from Indian Statistical Institute and his Ph.D. work was on the development of Printed Bangla OCR system. He did his Post Doctoral research on the segmentation of touching English numerals at INRIA (Institut National de Recherche en Informatique et en Automatique), France. During July 1997–January 1998 he visited GSF-Forschungszentrum fur Umwelt und Gesundheit GmbH, Germany to work as a guest scientist in a project on image analysis. From January 1997, he is a Faculty member of the Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata. His primary research is Digital Document Processing. He has published 163 research papers in various international journals, conference proceedings and edited volumes. In 1995, he received student best paper award from Chennai Chapter of Computer Society of India. He received a merit certificate from Indian Science Congress Association in 1996. Because of his significant impact in the Document Analysis research domain of Indian language, TC-10 and TC-11 committees of IAPR (International Association for Pattern Recognition) presented ‘ICDAR Outstanding Young Researcher Award’ to Dr. Pal in 2003. In 2005–2006 Dr. Pal has received JSPS fellowship from Japan government. Dr. Pal has been serving as a program committee member of many conferences including International Conference on Document Analysis and Recognition (ICDAR), International Workshop on Document Image Analysis for Libraries (DIAL), International Workshop on Frontiers of Handwritten Recognition (IWFHR), International Conference on Pattern recognition (ICPR) etc. Also, he is the Asian PC-Chair for 10th ICDAR to be held at Barcelona, Spain in 2009. He has served as the guest editor of special issue of VIVEK journal on Document image analysis of Indian scripts. Also currently he is co-editing a Special issue of the journal of Electronic Letters on Computer Vision and Image Analysis. He is a life member of IUPRAI (Indian unit of IAPR) and senior life member of Computer Society of India. Josep Lladós received the degree in Computer Sciences in 1991 from the Universitat Politècnica de Catalunya and the Ph.D. degree in Computer Sciences in 1997 from the Universitat Autònoma de Barcelona (Spain) and the Universitè Paris 8 (France). Currently he is an Associate Professor at the Computer Sciences Department of the Universitat Autònoma de Barcelona and a staff researcher of the Computer Vision Center, where he is also the director since January 2009. He is the head of the Pattern Recognition and Document Analysis Group (2009SGR-00418). He is chair holder of Knowledge Transfer of the UAB Research Park and Santander Bank. His current research fields are document analysis, graphics recognition and structural and syntactic pattern recognition. He has been the head of a number of Computer Vision R+D projects and published more than 100 papers in national and international conferences and journals. J. Lladós is an active member of the Image Analysis and Pattern Recognition Spanish Association (AERFAI), a member society of the IAPR. He is currently the chairman of the IAPR-ILC (Industrial Liaison Committee). Formerly he served as chairman of the IAPR TC-10, the Technical Committee on Graphics Recognition, and also he is a member of the IAPR TC-11 (reading Systems) and IAPR TC-15 (Graph-based representations). He serves on the Editorial Board of the ELCVIA (Electronic Letters on Computer Vision and Image Analysis) and the IJDAR (International Journal in Document Analysis and Recognition), and also a PC member of a number of international conferences. He was the recipient of the IAPR-ICDAR Young Investigator Award in 2007. He was the general chair of the International Conference on Document Analysis and Recognition (ICDAR’2009) held in Barcelona in July 2009, and co-chair of the IAPR TC-10 Graphics Recognition Workshop of 2003 (Barcelona), 2005 (Hong Kong), 2007 (Curitiba) and 2009 (La Rochelle). Josep Lladós has also experience in technological transfer and in 2002 he created the company ICAR Vision Systems, a spin-off of the Computer Vision Center working on Document Image Analysis, after winning the entrepreneurs award from the Catalonia Government on business projects on Information Society Technologies in 2000.
Corresponding Author: Roy, P. P.; Computer Vision Centre, Universitat Autonoma de BarcelonaSpain; email: 2partharoy@gmail.com
Appears in Collections:Journal Publications [CS]

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