  This article presents a new method of segmenting grayscale images by
minimizing Shannon's neutrosophic entropy. For the proposed segmentation
method, the neutrosophic information components, i.e., the degree of truth, the
degree of neutrality and the degree of falsity are defined taking into account
the belonging to the segmented regions and at the same time to the separation
threshold area. The principle of the method is simple and easy to understand
and can lead to multiple thresholds. The efficacy of the method is illustrated
using some test gray level images. The experimental results show that the
proposed method has good performance for segmentation with optimal gray level
thresholds.
