Abstract
The available visual information is quickly growing now a days, it is the reason of the emerging of a new research field, oriented to the automatic retrieval of this kind of information. These systems usually uses perceptual features of the images (color, shape, texture,...). There is an important gap between the features used by the CBIR systems and the human perception of the information of an image. This work introduces a technique to extract significant perceptual regions of an image. The developed algorithm uses a bidimensional active model, active nets, these nets are guided by the chromatic components of a perceptual color space of the tested image. The restriction to only chromatic information made the fitting of an active net to the significant perceptual regions more tolerant to illumination problems of the image. The final objective will be to associate significant perceptual regions with semantic descriptors of the objects present in an image.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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
del Bimbo, A.: Visual Information Retrieval. Morgan Kaufmann Plublisers, Inc. San Francisco (1999)
Smeulders, A., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-Based Image Retrieval at the End of the Early Years. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(12), 1349–1380 (1999)
Santini, S.: Exploratory Image Databases: Content-Based Retrieval. Academic Press, London (2001)
Rui, Y., Huang, T., Mehrotra, S.: Image Retrieval: Current Techniques, Promising Directions, and Open Issues. Journal of Visual Communications and Image Representation 10, 39–62 (1999)
Brunelli, R., Mich, O.: Image Retrieval by Examples. IEEE Transactions on Multimedia 2(3), 164–171 (2000)
del Bimbo, A., Pala, P.: Visual Image Retrieval by Elastic Matching of User Sketches. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(2) (1997)
Gevers, T.: Color Image Invariant Segmentation and Retrieval. Ph. D., Wiskunde, Informatica, Natuurkunde and Sterrenunde (WINS), Amsterdam (1996)
Colombo, C., del Bimbo, A.: Color-Induced Image Representation and Retrieval. Pattern Recognition 32, 1685–1695 (1999)
Berreti, S., del Bimbo, A., Pala, P.: Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing. IEEE Transactions on Multimedia 2(4), 225–239 (2000)
Pala, P., Santini, S.: Image Retrieval by Shape and Texture. Pattern Recognition 32, 517–527 (1999)
Bro-Nielsen, M.: Active Nets and Cubes. Morten Bro-Nielsen: Active Nets and Cubes, IMM Tech. Rep. 94-13 (1994)
Ansia, F.M., Penedo, M.G., Mariño, C., López, J., Mosquera, A.: Automatic 3D Shape Reconstruction of Bones using Active Nets Based Segmentation. In: 15th International Conference on Pattern Recognition, Bacelona (2000)
Ansia, F.M., Penedo, M.G., Mariño, C., López, J., Mosquera, A.: Morphological Analysis with Active Nets. In: 4th Internation Conference on Advances in Pattern Recognition and Digital Techniques, ICAPRDT1999, Calcutta (1999)
Sangwine, S., Horne, R.: The Colour Image Procesing Handbook. Chapman & Hall, Boca Raton (1998)
Weisstein, E. W.: K-Means Clustering Algorithm. MathWorld–A Wolfram Web Resource (2004), http://mathworld.wolfram.com/K-MeansClusteringAlgorithm.html
Colombo, C., del Bimbo, A.: Visible Image Retrieval. In: Castelli, V., Bergman, L.D. (eds.) Image Databases: Search and Retrieval of Digital Imagery, pp. 11–33. John Wiley Sons, Inc.Chichester (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
García-Pérez, D., Mosquera, A., Ortega, M., Penedo, M.G. (2004). Significant Perceptual Regions by Active-Nets. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_98
Download citation
DOI: https://doi.org/10.1007/978-3-540-30125-7_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23223-0
Online ISBN: 978-3-540-30125-7
eBook Packages: Springer Book Archive