Robust Gray-Level Histogram Gaussian Characterisation

One of the most utilised criteria for segmenting an image is the gray level values of the pixels in it. The information for identifying similar gray values is usually extracted from the image histogram. We have analysed the problems that may arise when the histogram is automatically characterised in terms of multiple Gaussian distributions and solutions have been proposed for special situations that we have named degenerated modes. The convergence of the method is based in the expectation maximisation algorithm and its performance has been tested on images from different application fields like medical imaging, robotic vision and quality control.