An Efficient Image Segmentation Algorithm Using Neutrosophic Graph Cut

Symmetry

Yanhui Guo¹  Abdulkadir Şengür²  Yaman Akbulut²  Florentin Smarandache³  Rong Xia⁴ 

[1] Department of Computer Science, University of Illinois at Springfield, Springfield, IL 62703, USA;Department of Electrical and Electronics Engineering, Firat University, 23119 Elazig, Turkey;Mathematics & Science Department, University of New Mexico, Gallup, NM 87301, USA;Oracle Corporation, Westminster, CO 80021, USA;

关键词: image segmentation;    neutrosophic set;    graph cut;    indeterminate filtering;   

DOI  :  10.3390/sym9090185

来源: DOAJ

【 摘 要 】

Segmentation is considered as an important step in image processing and computer vision applications, which divides an input image into various non-overlapping homogenous regions and helps to interpret the image more conveniently. This paper presents an efficient image segmentation algorithm using neutrosophic graph cut (NGC). An image is presented in neutrosophic set, and an indeterminacy filter is constructed using the indeterminacy value of the input image, which is defined by combining the spatial information and intensity information. The indeterminacy filter reduces the indeterminacy of the spatial and intensity information. A graph is defined on the image and the weight for each pixel is represented using the value after indeterminacy filtering. The segmentation results are obtained using a maximum-flow algorithm on the graph. Numerous experiments have been taken to test its performance, and it is compared with a neutrosophic similarity clustering (NSC) segmentation algorithm and a graph-cut-based algorithm. The results indicate that the proposed NGC approach obtains better performances, both quantitatively and qualitatively.

【 授权许可】

Unknown