134Accesses
6Altmetric
Abstract
Recognition of primitives in technical drawings is the first stage in their higher level interpretation. It calls for processing of voluminous scanned raster files. This is a difficult task if each pixel must be addressed at least once, as required by Hough transform or thinning-based methods. This work presents a set of algorithms that recognize drawing primitives by examining the raster file sparsely. Bars (straight line segments), arcs, and arrowheads are identified by the orthogonal zig-zag, perpendicular Bisector tracing, and self-supervised arrowhead recognition algorithms, respectively. The common feature of these algorithms is that rather than applying massive pixel addressing, they recognize the sought primitives by screening a carefully selected sample of the image and focusing attention on identified key areas. The sparse-pixel-based algorithms yield high quality recognition, as demonstrated on a sample of engineering drawings.
This is a preview of subscription content,log in via an institution to check access.
Access this article
Subscribe and save
- Get 10 units per month
- Download Article/Chapter or eBook
- 1 Unit = 1 Article or 1 Chapter
- Cancel anytime
Buy Now
Price includes VAT (Japan)
Instant access to the full article PDF.
Similar content being viewed by others
References
Antoine D, Collin S, Tombre C (1990) Analysis of technical documents. The REDRAW system. Pre-Proceedings of the IAPR Workshop on Syntactic and Structural Pattern Recognition, Murray Hill, NJ, pp 1–20
Chai I, Dori D (1992) Extraction of text boxes from engineering drawings. Proceedings of the SPIE/IS&T Symposium on Electronic Imaging Science and Technology, Conference on Character Recognition and Digitizer Technologies. San Jose, Calif, 9–14 February 1992
Chai I, Dori D (1992) Orthogonal zig-zag: an effcient method for extracting bars in engineering drawings. In: Arcelli C, Cordella LP, Sanniti diBaja (eds) Visual Form. Plenum, New York pp. 127–136
Collin S, Colnet D (1991) Analysis of dimensions in mechanical engineering drawings. Proc. Machine Vision Applications. 105–108.
Colin S, Vaxiviere P (1991) Recognition and use of dimensioning in digitized industrial drawings. Proceedings of the First International Conference on Document Analysis and Recognition. IEEE Computer Society, Saint Malo, France
Conker RS (1988) Dual plane variation of the Hough transform for detecting non-concentric circles of different radii. Computer Vision, Graphics and Image Processing 43:115–132
Csink L (1989) On the recognition of elements appearing in a circuit diagram, Proceedings of the 2nd Hungarian AI Conference, Budapest
Dori D (1989) A syntactic geometric approach to recognition of dimensions in engineering machine drawings. Computer Vision, Graphics Image Processing 47:1–21
Dori D (1991) Self-structural syntax-directed pattern recognition of dimensioning components in engineering drawings. In Baird HS, Bunke H, Yamamoto K (eds) Springer, Berlin Heidelberg New York
Dori D (1992) Dimensioning analysis: a step towards automatic high level understanding of engineering drawings. Commun ACM October, pp 92–103
Fahn CS, Wang JF, Lee YL (1988) A topology-based component extractor for understanding electronic circuit diagrams. Computer Vision, Graphics Image Processing 44:119–138
Fukuda Y (1982) Primary algorithm for the understanding of logic circuit diagrams. Proc 6th ICPR, Munich, pp 706–709
Furuta M, Kase N, Emori S (1984) Segmentation and recognition of symbols for handwritten piping and instrument diagram. Proc 7th ICPR, Montreal, pp 612–614
Haralick RM, Shapiro L (1992) Computer and robot vision. Addison Wesley Reading
Harris JF, Kittler J, Llewellyn B, Preston G (1982) A modular system for interpreting binary pixel representation of linestructured data. In: Pattern recognition: theory and applications. D. Reidel, Dordrecht, pp 311–351
Hunt DJ, Nolte LW (1988) Performance of the Hough transform and its realtionship to statistical signal detection theory. Computer Vision, Graphics Image Processing 43:221–238
Illingworth J, Kittler J (1987) The adaptive Hough transform. IEEE Trans Pattern Analysis Machine Intelligence 9:690–697
Josep SH, Pridmore TP (1992) Knowledge directed interpretation of mechanical engineering drawings. IEEE Trans Pattern Analysis Machine Intelligence 14:928–940
Kasturi R, Bow ST, El-Masri W, Shah J, Gattiker JR, Mokate UB (1990) A system for interpretation of line drawings. IEEE Trans Pattern Analysis Machine Intelligence 12:987–991
Kimme C, Ballard DH, Slansky J (1975) Finding circles by an array of accumulators. CACM 18:120–122
King AK (1988) An Expert system facilitates understanding the paper engineering drawings, Proc IASTED International Symposium Expert Systems Theory and Their Applications, Los Angeles. ACTA Press, Anaheim, pp 169–172
Lin X, Shimotsuji S, Minoh M, Sakai T (1985) Efficient diagram understanding with characteristic pattern detection. Computer Vision, Graphics Image processing 30:84–106
Nagasami V, Langrana NA (1990) Engineering drawing processing and vectorization system. Computer Vision, Graphics Image Processing 49:379–397
O'Gorman L, Sanderson AC (1984) The converging squares algorithm: an efficient method for locating peaks in multidimensions. IEEE Trans Pattern Analysis Machine Intelligence 7:280–288
Preiss K (1984) Constructing the solid representation from engineering projections. Computers Graphics 8:381–389
Sato T, Tojo A (1982) Recognition and understanding of handdrawn diagams. Proc 6th ICPR, Munich, pp 674–677
Smith B, Wellington J (1986) Initial graphics exchange specification (IGES), version 3.0. National Institute os Standards NSBIR 86-3359
Takaji M, Konishi T, Yamada M (1982) Automatic digitizing and processing method for the printed circuit pattern drawings, Proc 6th ICPR, Munich
Therrien C (1989) Decision estimation and classification. Wiley, New York
Tombre K, Vaxiviere P (1991) Structure, syntax and semantics in technical document recognition. Proc First International Conference on Document Analysis and Recognition, IEEE Computer Society, Saint Malo, France
Wesley MA, Markowski G (1981) Fleshing out projections, IBM J Res Dev 26:934–953
Author information
Authors and Affiliations
Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology, 32000, Haifa, Israel
Dov Dori
Department of Computer Science, University of Kansas, 66045, Lawrence, KS, USA
Yubin Liang, Joseph Dowell & Ian Chai
- Dov Dori
You can also search for this author inPubMed Google Scholar
- Yubin Liang
You can also search for this author inPubMed Google Scholar
- Joseph Dowell
You can also search for this author inPubMed Google Scholar
- Ian Chai
You can also search for this author inPubMed Google Scholar
Rights and permissions
About this article
Cite this article
Dori, D., Liang, Y., Dowell, J.et al. Sparse-pixel recognition of primitives in engineering drawings.Machine Vis. Apps.6, 69–82 (1993). https://doi.org/10.1007/BF01211932
Issue Date:
Share this article
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative