The paper presents some aspects of the (gray level) image binarization methods used in artificial vision systems. It is introduced a new approach of gray level image binarization for artificial vision systems dedicated to industrial automation – temporal thresholding. In the first part of the paper are extracted some limitations of using the global optimum thresholding in gray level image binar...

Image thresholding is a challenging task in image processing field. Many efforts have already been made to propose universal, robust methods to handle a wide range of images. This paper introduces a new optimization-based thresholding approach. The optimizer, Differential Evolution (DE) algorithm, minimizes dissimilarity between the input grey-level image and the bi-level (thresholded) image. T...

Image thresholding plays very important role in many computer vision and image processing applications. Segmentation based on gray level histogram thresholding consists of a method that divides an image into two regions of interest; object and background. In image processing, we deal with many ambiguous situations. Fuzzy set theory is a useful mathematical tool for handling the ambiguity or unc...

Image thresholding is one of the most powerful techniques for image segmentation, but it is not always satisfactory in applications under uneven illuminations. Adaptive image thresholding is used to find the optimal window for solving the illumination problem. In this paper, a novel window selection method for adaptive local thresholding is proposed. Based on simulated annealing, the proposed a...