This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Indexing of Technical Line Drawing Databases
August 1999 (vol. 21 no. 8)
pp. 737-751

Abstract—Image indexing, namely, the problem of retrieving content information from images in response to queries, is a key problem underlying the operations in image databases. In this paper we present a method of indexing for 3D object queries in a database of a class of images called technical line drawings. Indexing is achieved as a combination of query-specific region selection and object recognition. The selection phase isolates relevant images and the regions in these images that are likely to contain the queried object. This is done using text information in the query and a grouping mechanism that is guaranteed to isolate single-object containing regions for the class of technical line drawing images. The grouping mechanism is an adaptation of Waltz relaxation to an extended junction set derived by analyzing the physically plausible ways in which interpretation lines interact with object contours. Model-based object recognition then confirms the presence of the part at the selected location using geometrical description of the queried 3D object. Results are shown that indicate that query-specific selection is very effective for reducing the search during indexing while lowering the chance of false positives and negatives.

[1] A. Karve, “Xsoft Provides Total Document Recall,” LAN Magazine, vol. 9, pp. 176, Aug. 1994.
[2] “Documentum Enterprise Document Management System,” The Workgroup Computing Report: Seybold Group, Aug. 1994.
[3] “BRS Introduces Windows Toolkit,” DBMS, Jan. 1994.
[4] “Basisplus Reported to SGI,” The Seybold Report on Publishing Systems, May 1994.
[5] Steve Zurier, “Finding Your Way through Imaging Maze,” Goverment Computer News, vol. 13, p. 6, Sept. 1994.
[6] R.M. Haralick and D. Queeney, “Understanding Engineering Drawings,” Computer Vision, Graphics, and Image Processing, vol. 20, pp. 244-258, 1982.
[7] D. Dori et al., “Sparse-Pixel Recognition of Primitives in Engineering Drawings,” Machine Vision and Applications, vol. 6, pp. 69-92, June 1993.
[8] A.K. Das and H. Langrana, “Recognition of Dimension Sets and Integration with Vectorized Engineering Drawings,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 347-350, 1995.
[9] C.P. Lai and R. Kasturi, “Detection of Dimension Sets in Engineering Drawings,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, pp. 848-855, 1994.
[10] L.A. Fletcher and R. Kasturi, “A Robust Algorithm for Text String Separation from Mixed Text/Graphics Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 10, pp. 910-918, Nov. 1988.
[11] J. Malik, “Interpreting Line Drawings of Curved Objects,” Proc. Int'l J. Computer Vision, vol. 1, pp. 73-103, 1987.
[12] A. Mackworth, “Interpreting Pictures of Polyhedral Scenes,” Artificial Intelligence, vol. 4, pp. 121-137, 1973.
[13] D. Waltz, “Generating Semantic Descriptions from Drawing of Scenes with Shadows,” Technical Report AI-TR-271, Massachusetts Inst. Tech nology, 1972.
[14] M. Straforini et al., “The Recovery and Understanding of a Line Drawing from Indoor Scenes,” IEEE Trans. Pattern Analysis and Machnine Intelligence, vol. 14, pp. 298-303, Feb. 1992.
[15] O. Hori et al., “Line Drawing Interpretation Using Probabilistic Relaxation,” Machine Vision and Applications,” vol. 6, pp. 100-109, June 1993.
[16] R. Kasturi, S.T. Bow, W. El-Masri, J. Shah, J.R. Gattikermes, and U.B. Mokate, "A System for Interpretation of Line Drawings," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 10, pp. 978-992, Oct. 1990.
[17] C. Ah-Soon and K. Tobre, “A Step Towards Reconstruction of 3D Models from Engineering Drawings,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 331-334, 1995.
[18] M. Weiss and D. Dori, “A Scheme for 3D Object Reconstruction from Dimensioned Orthographic Views,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 335-338, 1995.
[19] I. Lee et al., “A Study on a Method of Dividing Machine Parts into Functional Groups for Technical Illustrations,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 886-889, 1993.
[20] B. Yu, “Automatic Understanding of Symbol-Connected Diagrams,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 803-806, 1995.
[21] O. Lorenz and G. Monagan, “Retrieval of Line Drawings,” Third Ann. Symp. Document Analysis and Information Retrieval, pp. 461-468, Apr. 1994.
[22] P.H. Winston, Artificial Intelligence. Reading, Mass.: Addison-Wesley, 1984.
[23] O. Hori and D. Doermann, “Robust Table-Form Structure Analysis Based on Box-Driven Reasoning,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 218-221, 1995.
[24] E. Green and M. Krishnamurthy, “Model-Based Analysis of Printed Tables,”Proc. Proc. Int'l Conf. Document Analysis and Recognition, pp. 214-217, 1995.
[25] S. Chandan and R. Kasturi, Structural“Recognition of Tabulated Data,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 516-519, 1993.
[26] T. Watanabe, Q. Luo, and N. Sugie, “Toward a Practical Document Understanding of Table-Form Documents, Its Framework and Knowledge Representation,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 510-515, 1993.
[27] L.G. Roberts, “Machine Perception of Three-Dimensional Objects,” Opt. and Electro-Opt. Information Processing, Tippet et al., eds, pp. 159-197. Cambridge, Mass.: Massachusetts Inst. Technology Press, 1966.
[28] A. Guzman, “Computer Recognition of Three-Dimensional Objects in a Scene,” Technical Report MAC-TR-59, Massachusetts Inst. Technlogy, 1968.
[29] D.A. Huffman, “Realizable Configurations of Lines in Pictures of Polyhedra,” Machine Intelligence, D. Mitchie, ed., vol. 8, pp. 493-509, 1977.
[30] M.B. Clowes, “On Seeing Things,” Artificial Intelligence, vol. 2, pp. 79-116, 1971.
[31] G. Falk, “Interpretation of Imperfect Line Data as a Three-Dimensional Scene,” Artificial Intelligence, vol. 4, pp. 101-144, 1972.
[32] I. Chakravarthy, “A Generalized Line and Junction Labeling Scheme with Applications to Scene Analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 1, pp. 202-205, 1979.
[33] R. Basri, "On the Uniqueness of Correspondence Under Orthographic and Perspective Projections," A.I. Memo No. 1333, Massachusetts Institute of Technology, Artificial Intelligence Laboratory, Dec. 1991.
[34] S. Ullman and R. Basri, "Recognition by Linear Combinations of Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, pp. 992-1006, 1991.
[35] W.E.L. Grimson, Object Recognition by Computer. MIT Press, 1990.

Index Terms:
Image databases, technical line drawings, line-labeling, region selection, grouping, recognition, search.
Citation:
Tanveer Syeda-Mahmood, "Indexing of Technical Line Drawing Databases," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 8, pp. 737-751, Aug. 1999, doi:10.1109/34.784287
Usage of this product signifies your acceptance of the Terms of Use.