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Multiclass histogram-based thresholding using kernel density estimation and scale-space representations
We present a method for multiclass thresholding of histograms whose modes may overlap so strongly that they merge into a unimodal distribution. The histogram is approximated by a nonparametric kernel density (KD) estimate, a mixture of Gaussians with one component per bin and a common bandwidth, who
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