By J. Torreao
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A) (b) Fig. 1. A representative hemispherical stereo pair; (a) left image; (b) right image. 1 Identification of high contrasted textures The textures produced by the leaves of the trees under analysis do not display spatial distributions of frequencies nor textured patterns; they are rather high contrasted areas without any spatial orientation. e. statistical second-order moments. One of the simplest is the variance. It is a measure of intensity contrast defined in our approach as in (Gonzalez & Woods, 2008; Herrera, 2010).
Olson, E. (2008). Robust and Efﬁcient Robotic Mapping, PhD thesis, Massachusetts Institute of Technology, Cambridge, MA, USA. , Kittler, J. & Petrou, M. (1994). Using focus of attention with the hough transform for accurate line parameter estimation, Pattern Recognition 27(9): 1127–1134. Robbins, H. & Monro, S. (1951). A stochastic approximation method, The Annals of Mathematical Statistics 22(3): 400–407. Rosenfeld, A. (1969). Picture processing by computer, ACM Comput. Surv. 1: 147–176. Simhon, S.
For a pixel belonging to one of such areas the R coefficient should be low because of its homogeneity. This is a previous criterion for identifying such areas, where the 'low' concept is mapped assuming that R should be less than the previous threshold T1. Nevertheless, this is not sufficient because there are other different areas which are not sky or grass fulfilling this criterion. Therefore, we apply a classification technique based on the combination of the parametric Bayesian estimator (PB) and Parzen window (PZ) approaches.