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.
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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
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DOI: https://doi.org/10.1007/978-3-540-30125-7_98
Publisher Name: Springer, Berlin, Heidelberg
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