A New Image Segmentation Method Based on Fractional-Varying-Order Differential
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Graphical Abstract
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Abstract
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 differential is proposed. This model introduces an adaptive coefficient to set disparate differential order intervals 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 similarity (JS) rate, and Dice coefficient (DC) rate to measure the pros and cons of our model. The experimental results show that our method is improved on the original basis, which is more conducive to us to obtain more image details and obtain better segmentation results.
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