In this paper we present a hierarchical learning method to segment natural colour images combining the perceptual information of three natures: colour, texture, and homogeneity. Human knowledge is incorporated to a hierarchical categorisation process, where each nature features are independently categorised. Final segmentation is achieved through a refinement process using the categorisation information from each segment. Experiments are performed using the Berkeley Segmentation Dataset achieving good results even when comparing them to other significant methods. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Díaz-Pernas, F. J., Antón-Rodríguez, M., Díez-Higuera, J. F., Martínez-Zarzuela, M., González-Ortega, D., Boto-Giralda, D., & De La Torre-Díez, I. (2010). Natural scene segmentation method through hierarchical nature categorization. In Advances in Intelligent and Soft Computing (Vol. 79, pp. 53–60). https://doi.org/10.1007/978-3-642-14883-5_7
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