Image analysis using modified multifractal measure based on sigmoid function

In this paper we propose the new multifractal measure inspired by sigmoid activation function usually used in neural networks. By using new measure the Hölder exponent and multifractal spectrum are determined in classical way. New measure is applied to image processing, especially in texture classification. It was shown that by changing the slope of the sigmoid function different details can be extracted from analyzed image. Initial results are promising and indicate to high potential of new measure in image processing.