Fast Single-Parameter Energy Function Thresholding for Image Segmentation Based on Region Information

To solve the problems of image threshold segmentation based on weak continuous constraint theory, running time is long, and two parameters need to be selected manually, therefore a fast single-parameter energy function thresholding for region information (FSEFTISRI) proposed in this paper. The FSEFTISRI algorithm uses simple linear iterative clustering (SLIC) technology pre-block image, extract super-pixels, then map super-pixels interval type-2 fuzzy set (IT2FS), so as construct search optimal threshold, adaptively select penalty through class uncertainty theory. On non-destructive testing (NDT) database Berkeley datasets benchmarks (BSDS), compared with five related algorithms. average misclassification error (ME) NDT BSDS are 0.0466 0.0039, respectively. results show that has acquired more satisfactory visual effect evaluation index, shorter, which shows effectiveness FSEFTISRI.