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Finding Perceptually Closed Paths in Sketches and Drawings
April 2003 (vol. 25 no. 4)
pp. 475-491
Eric Saund, IEEE

Abstract—Closed or nearly closed regions are an important form of perceptual structure arising both in natural imagery and in many forms of human-created imagery including sketches, line art, graphics, and formal drawings. This paper presents an effective algorithm especially suited for finding perceptually salient, compact closed region structure in hand-drawn sketches and line art. We start with a graph of curvilinear fragments whose proximal endpoints form junctions. The key problem is to manage the search of possible path continuations through junctions in an effort to find paths satisfying global criteria for closure and figural salience. We identify constraints particular to this domain for ranking path continuations through junctions, based on observations of the ways that junctions arise in line drawings. In particular, we delineate the roles of the principle of good continuation versus maximally turning paths. Best-first bidirectional search checks for the cleanest, most obvious paths first, then reverts to more exhaustive search to find paths cluttered by blind alleys. Results are demonstrated on line drawings from several sources including line art, engineering drawings, sketches on whiteboards, as well as contours from photographic imagery.

[1] S. Ablamayko, A. Gorelik, and S. Medvedev, “From Recognized Engineering Drawings to 3D Object Reconstruction,” Proc. Third IAPR Int'l Workshop Graphics Recognition, pp. 313-319, 1999.
[2] R.O. Canham, S.L. Smith, and A.M. Tyrrell, “Recognition and Grading of Severely Distorted Geometric Shapes from within a Complex Figure,” Pattern Analysis and Applications, vol. 3, no. 4, pp. 335-347, 2000.
[3] S. Casadei and S. Mitter, “Beyond the Uniqueness Assumption: Ambiguity Representation and Redundancy Elimination in the Computation of a Covering Sample of Salient Contour Cycles,” Computer Vision and Image Understanding, vol. 76, no. 1, pp. 19-35, 1999.
[4] J. Dolan and E. Riseman, “Computing Curvilinear Structure by Token-Based Grouping,” Proc. Conf. Computer Vision and Pattern Recognition, pp. 264-270, 1992.
[5] J. Elder and S. Zucker, “Computing Contour Closure,” Proc. European Conf. Computer Vision, pp. 399-412, 1996.
[6] M. Fleck, “Local Rotational Symmetries,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 332-337, 1986.
[7] D. Huttenlocher and P. Wayner, “Finding Convex Edge Groupings in an Image,” Int'l J. Computer Vision, vol. 8, no. 1, pp. 7-27, 1992.
[8] D.W. Jacobs, "Robust and Efficient Detection of Salient Convex Groups," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, pp. 23-37, Jan. 1996.
[9] J. Jorge and M. Fonseca, “A Simple Approach to Recognize Geometric Shapes Interactively,” Proc. Third IAPR Int'l Workshop Graphics Recognition, pp. 251-258, 1999.
[10] S. Mahamud, K. Thornber, and L. Williams, “Segmentation of Salient Closed Contours From Real Images,” Proc. Int'l Conf. Computer Vision, 1999.
[11] R. Mohan and R. Nevaita, “Perceptual Organization for Scene Segmentation and Description,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 11, pp. 1121-1139, Nov. 1992.
[12] T. Pavlidis, “An Automatic Beautifier for Drawings and Illustrations,” Proc. ACM SIGGRAPH '85, vol. 19, no. 3, pp. 225-234, 1985.
[13] S. Sarkar and K.L. Boyer, "Integration, Inference, and Management of Spatial Information Using Bayesian Networks: Perceptual Organization," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 3, pp. 256-274, Mar. 1993. Special Section on Probabilistic Reasoning.
[14] E. Saund, “Symbolic Construction of a 2D Scale-Space Image,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 8, pp. 817-830, 1990.
[15] E. Saund, “Putting Knowledge Into a Visual Shape Representation,” Artificial Intelligence, vol. 54, pp. 71-119, 1992.
[16] E. Saund, “Labeling of Curvilinear Structure Across Scales By Token Grouping,” Proc. Conf. Computer Vision and Pattern Recognition, pp. 257-263, 1992.
[17] E. Saund, “Bringing the Marks on a Whiteboard to Electronic Life,” Proc. Cooperative Buildings—Integrating Information, Organizations, and Architecture: Second Int'l Workshop, CoBuild '99 (Lecture Notes in Computer Science 1670), N. Streitz, J. Siegel, V. Hartkopf, and S. Konimi, eds., Springer, 1999.
[18] E. Saund and T. Moran, “A Perceptually-Supported Sketch Editor,” Proc. ACM Symp. User Interface Software and Technology, pp. 175-184, 1994.
[19] E. Saund and T. Moran, “Perceptual Organization in an Interactive Sketch Editing Application,” Proc. Int'l Conf. Computer Vision, pp. 597-604, 1995.
[20] E. Saund, J. Mahoney, D. Fleet, and D. Larner, “Perceptual Organization as a Foundation for Graphics Recognition,” Proc. Fourth IAPR Int'l Workshop Graphics Recognition, Sept. 2001.
[21] S. Ullman, “Visual Routines,” Cognition, vol. 18, pp. 97-159, 1984.

Index Terms:
Contour closure, closed path, perceptual organization, Gestalt laws, sketch interpretation, line art analysis, graphics recognition.
Citation:
Eric Saund, "Finding Perceptually Closed Paths in Sketches and Drawings," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 4, pp. 475-491, April 2003, doi:10.1109/TPAMI.2003.1190573
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