Abstract
We present a new method for image retrieval by shape similarity able to deal with real images with not uniform background and possible touching/occluding objects. First of all we perform a sketch-driven segmentation of the scene by means of a Deformation Tolerant version of the Generalized Hough Transform (DTGHT). Using the DTGHT we select in the image some candidate segments to be matched with the user sketch. The candidate segments are then matched with the sketch checking the consistency of the corresponding shapes. Finally, background segments are used in order to inhibit the recognition process when they cannot be perceptually separated from the object.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Anelli, M., Micarelli, A., Sangineto, E.: A deformation tolerant version of the generalized hough transform for image retrieval. In: 15th European Conference on Artificial Intelligence (ECAI 2002), Lyon, France (2002)
Anelli, M., Micarelli, A., Sangineto, E.: A new content based image retrieval method based on a sketch-driven interpretation of line segments. In: 18th International Joint Conference on Artificial Intelligence (IJCAI 2003), Acapulco, Mexico (2003)
Ballard, D.H.: Generalizing the Hough Transform to detect arbitrary shapes. Pattern Recognition 13(2), 111–122 (1981)
Canny, J.: A computational approach to edge detection. IEEE Trans. on PAMI 8(6), 679–698 (1986)
Colombo, C., Del Bimbo, A.: Visible image retrieval. In: Bergman, L., Castelli, V. (eds.) Image Data Bases - Search and Retrieval of Digital Imagery, ch. 2, pp. 11–33. Wiley, Chichester (2002)
Crimmins, T.: The geometric filter for speckle reduction. Applied optics 24(10) (1985)
Del Bimbo, A., Pala, P.: Visual image retrieval by elastic matching of user sketches. IEEE Trans. on PAMI 19(2), 121–132 (1997)
Flickner, M., et al.: Query by image and video content: the QBIC system. IEEE Computer 28(9), 23–32 (1995)
Jain, A.K., Zhong, Y., Lakshmanan, S.: Object matching using deformable templates. IEEE Trans. on PAMI 18, 267–278 (1996)
Koffka, K.: Principles of Gestalt Psychology. Harcourt, Brace and World, New York (1935)
Mokhtarian, F.: Silhouette-based isolated object recognition through curvature scale-space. IEEE Trans. on PAMI 17(5), 539–544 (1995)
Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. on PAMI 22(12), 1349–1380 (2000)
Ullman, S.: High–level Vision. In: Object Recognition and Visual Cognition. A Bradford Book. The MIT Press, Cambridge (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Anelli, M., Micarelli, A., Sangineto, E. (2003). Content Based Image Retrieval for Unsegmented Images. In: Cappelli, A., Turini, F. (eds) AI*IA 2003: Advances in Artificial Intelligence. AI*IA 2003. Lecture Notes in Computer Science(), vol 2829. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39853-0_33
Download citation
DOI: https://doi.org/10.1007/978-3-540-39853-0_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20119-9
Online ISBN: 978-3-540-39853-0
eBook Packages: Springer Book Archive