High-Performance Preprocessing of Architectural Drawings for Legend Metadata Extraction via OCR
Pages 197 - 200
Abstract
This paper describes the results of an investigation into methods of preprocessing architectural plots to enable them to be processed very quickly via OCR, detecting the region containing the relevant metadata legend and obtaining it in machine-readable form for e.g. automated folding and filenaming applications. We show how a processing pipeline adapted to this type of content can vastly decrease processing time, maintaining acceptable accuracy. Initial results show a reduction in total processing time from 2--3 minutes to around 15 seconds for most documents encountered, with the folding orientation being correctly detected in 78% of cases and the legend region being completely detected in 60% of cases, high enough for the use-case at hand.
References
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Christian Ah-Soon and Karl Tombre. 1997. Variations on the Analysis of Architectural Drawings ICDAR 1997: Proceedings of the Fourth International Conference on Document Analysis and Recognition.
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S. Ahmed, M. Liwicki, M. Weber, and A. Dengel. 2011. Improved Automatic Analysis of Architectural Floor Plans ICDAR 2011: Proceedings of the 11th International Conference on Document Analysis and Recognition.
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L. A. Fletcher and R. Kasturi. 1988. A Robust Algorithm for Text String Separation from Mixed Text/Graphics Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 10, 6 (1988).
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J. Gllavata, R. Ewerth, and B. Freisleben. 2004. Text Detection in Images Based on Unsupervised Classification of High-Frequency Wavelet Coefficients. In ICPR 2004: Proceedings of the 17th International Conference on Pattern Recognition.
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M. Goebel, T. Hassan, E. Oro, and G. Orsi. 2013. ICDAR 2013 Table Competition. In ICDAR 2013: Proceedings of the 12th International Conference on Document Analysis and Recognition.
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Index Terms
- High-Performance Preprocessing of Architectural Drawings for Legend Metadata Extraction via OCR
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Information
Published In
August 2017
242 pages
ISBN:9781450346894
DOI:10.1145/3103010
- General Chair:
- Kenneth Camilleri,
- Program Chair:
- Alexandra Bonnici
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Association for Computing Machinery
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Publication History
Published: 31 August 2017
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DocEng '17
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DocEng '17 Paper Acceptance Rate 13 of 71 submissions, 18%;
Overall Acceptance Rate 194 of 564 submissions, 34%
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