DocumentCode
3528573
Title
Diagram Recognition: Domain Knowledge Based Approach
Author
Bashir, Rumaan ; Giri, Kaiser J.
Author_Institution
Dept. of Comput. Sci., Islamic Univ. of Sci. & Technnology, Awantipora, India
fYear
2013
fDate
21-23 Dec. 2013
Firstpage
445
Lastpage
449
Abstract
Information has become a very important resource of any organization and a great demand exists for speedily inputting the colossal amount of printed and handwritten information present on documents into the computer, which requires a lot of manual labour. Over the past few decades, electronic document management systems have turned out to be "beneficial to" and "popular in" the society. Profound research and development has been done in this field. Automatic pattern analysis & recognition systems have been & are being developed to analyze the contents of the documents. An important stage in this procedure is the automatic recognition of diagrams from the document. Diagram recognition being one of the main areas in the field of document analysis & pattern recognition is still an open area for researchers. Diagram recognition is a trivial task for humans, but the development of its computer based solution is tremendously difficult. Various subject-specific methods have been developed. In this paper, we present a novel cognitive approach for the recognition of offline typeset/machine-drawn diagrams by the identification of its symbols. The focus here is to use minimal amount of data for the purpose of recognition and to provide a general system for recognition of various types of diagrams. This involves the development of a Recognition Domain Knowledge Kernel. The algorithm proposed is independent of the size of the symbol used in the diagram. Based on the type of symbols present in the diagram, a diagram classification is made.
Keywords
document image processing; handwritten character recognition; automatic diagram recognition; automatic pattern analysis; document analysis; domain knowledge based approach; electronic document management systems; handwritten information; offline typeset/machine-drawn diagrams; pattern recognition systems; printed information; recognition domain knowledge kernel; subject-specific methods; Connectors; Image recognition; Image segmentation; Kernel; Knowledge based systems; Text analysis; Binarization; Cognitive; Diagram; Digitization; Feature Extraction; Normalization; Recognition; Recognition Domain Knowledge Kernel; Region Code; Skew;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Intelligence and Research Advancement (ICMIRA), 2013 International Conference on
Conference_Location
Katra
Type
conf
DOI
10.1109/ICMIRA.2013.94
Filename
6918871
Link To Document