Image histogram thresholding using gaussian kernel densit y estimation* (English) [Gauss olabilirlik degerlerine dayali goruntu histogrami esikleme]
2013 21st Signal Processing and Communications Applications Conference, SIU 2013
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27992
In this article, image histogram thresholding is carried out using the likelihood of a mixture of Gaussians. In the proposed approach, a prob ability density function (PDF) of the histogram is computed using Gaussian kernel density estimation in an iterative manner. The threshold is found by iteratively computing a mixture of Gaussians for the two clusters. This process is aborted when the current bin is assigned to a different cluster than its predecessor. The method does not envolve an exhaustive search. Visual examples of our segmentation versus Otsu's thresholding method are presented. © 2013 IEEE.
- Conference Paper 
Showing items related by title, author, creator and subject.
Turgut, E.; Gezici, S. (2013)In this paper, spectrum sensing in cognitive radio systems is studied for non-Gaussian channels in the presence of prior distribution uncertainty. In most practical cases, some amount of prior information about signals of ...
Cost minimization of measurement devices under estimation accuracy constraints in the presence of Gaussian noise Dulek, B.; Gezici, S. (2012)Novel convex measurement cost minimization problems are proposed based on various estimation accuracy constraints for a linear system subject to additive Gaussian noise. Closed form solutions are obtained in the case of ...
Ali, S.A.; Ince, E.A. (2007)The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for additive white Gaussian noise (AWGN) channels is not promising ...