OtsuAlgorithmus

The Otsu algorithm is a method for automatic image thresholding. Its purpose is to find an optimal threshold value to separate pixels into foreground and background classes. It works by minimizing the intra-class variance, which is the weighted variance of the pixel intensities within each class.

The algorithm assumes that the image contains two classes of pixels, typically foreground and background, and that their intensity distributions are bimodal. It iterates through all possible threshold values, from the minimum to the maximum intensity in the image. For each threshold, it calculates the probability of each class and the means of each class.

The variance within each class is then calculated. The algorithm seeks the threshold that minimizes the sum of the weighted intra-class variances. This minimum value indicates the best separation between the two classes. The Otsu algorithm is computationally efficient and widely used in image processing applications, especially when manual thresholding is not feasible. It is a non-parametric method and does not require any prior knowledge about the image content.