In this paper, the authors are devoted to design a new segmentation approach based on I-Ching operators in the framework of shadowed fuzzy C-means clustering. The I-Ching operators are innovative operators, which are evolved from ancient Chinese I-Ching philosophy. I-Ching operators include three kinds of operators, intrication operator, turnover operator, and mutual operator. These new operators are very flexible and efficient in evolution procedure. In this paper, the new operators are specifically designed to search for the optimal cluster centers of shadowed fuzzy C-means. Considering the local spatial information in image segmentation procedure, a new segmentation algorithm called I-Ching spatial shadowed fuzzy C-means (ICSSFCM) is proposed. Traditional segmentation approaches based on fuzzy C-means, shadowed fuzzy C-means, and spatial shadowed fuzzy C-means are compared with the proposed method. The experimental results show that the proposed ICSSFCM is very efficient approach not only in tackling the overlapping segments but also in suppressing the noise in images.