A New Image Segmentation Method Based on Fractional-Varying-Order Differential

• 作者: Yanshan Zhang Yuru Tian
• 来源期刊: 北京理工大学学报（英文版）
• 年，卷（期）: 2021,（3）
• 页码范围: 254-264
• 页数: 11页
• 语种: 英文
• DOI: 10.15918/j.jbit1004-0579.2021.028

摘要

In order to solve the problem of image segmentation with intensity inhomogeneity, a new partial differential equation image segmentation model based on fractional-varying-order differen-tial is proposed. This model introduces an adaptive coefficient to set disparate differential order in-tervals for pixel with different gray values and use fractional-varying-order differential to process the input image combined with the CV model, then use a variety of image segmentation evaluation indicators, such as true positive (TP) rate, false positive (FP) rate, precision (P), Jaccard similar-ity (JS) rate, and Dice coefficient (DC) rate to measure the pros and cons of our model. The ex-perimental results show that our method is improved on the original basis, which is more condu-cive to us to obtain more image details and obtain better segmentation results.