Abstract
The vision system of human beings is very sensitive to lines. Sketches composed of line drawings provide a useful representation for image structures, which can be used for recognition and which is capable of serving as intermediate data structures of images for further analysis. However, traditional schemes tackling the line detection problem for sketch generation are stuck to one of the two problems: lack of global supervision for line detection over an image or confinement of hard global constraints on the configuration of detected lines.In this paper, we propose an active sketch model for finding primary structures in the form of line drawings, overcoming shortcomings of the traditional schemes by combining local line finding techniques with supervision of a global saliency measure while imposing no global constraint on the configuration of the line drawings.Test results show that our model is able to sketch out lines in an image representing the most salient image discontinuity without imposing any shape or topology constraint on the sketch.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bruce, V., Hanna, E., Dench, N., Healy, P., Burton, A.: The importance of ’mass’ in line drawing of faces. Applied Cognitive Psychology 6, 619–628 (1992)
Saund, E.: Finding perceptually closed paths in sketches and drawings. IEEE Trans. Pattern Anal. Machine Intell. 25, 475–491 (2003)
Gao, Y., Leung, M.: Face recognition using line edge map. IEEE Trans. Pattern Anal. Machine Intell. 22, 764–779 (1998)
Prinet, V., De Song, M., Monga, O.: Scale selection for curvilinear structures detection from remote sensing images (2000)
Iqbal, Q., Aggarwal, J.: Image retrieval via isotropic and anisotropic mappings. Pattern Recognition Journal 35, 2673–2686 (2002)
Nevatia, R., Babu, K.: Linear feature extraction and description. Comput. Vis. Graph Image Processing 33, 257–269 (1980)
Duda, R., Hart, P.: Use of hough transform to detect lines and curves in pictures. Commun. ACM 15, 11–15 (1972)
Mumford, D., Shah, J.: Boundary detection by minimizing functionals. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 22–26 (1985)
Kass, M., Witkin, A., Terzopoulos, D.: Snake: active contour models. INT J Computer Vision, 321–331 (1988)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Machine Intell 8, 679–698 (1986)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, S., Xu, C., Lei, Q. (2006). Active Sketch for Finding Primary Structures in Images. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_89
Download citation
DOI: https://doi.org/10.1007/11875581_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
Online ISBN: 978-3-540-45487-8
eBook Packages: Computer ScienceComputer Science (R0)