多阈值交互式图像智能分割方法优化与仿真

Optimization and Simulation of Multi-Threshold Interactive Image Intelligent Segmentation Method

目前多阈值交互式图像分割方法没有对图像进行预处理,存在图像分割效果差与图像分割性能不佳的问题。提出基于Prewitt算法的多阈值交互式图像分割优化方法。方法首先利用自适应算法对图像进行去噪以及纹理处理,对图像进行增强,将增强后的图像进行交互式处理,即对图像进行标记和合并以此提高分割效果,最后在Prewitt算法的基础上优化阈值选取并进行图像分割,实现多阈值交互式图像分割优化。实验结果表明,所提方法的图像分割效果与分割性能较好,说明该方法的应用价值较高。

At present, the multi-threshold interactive image segmentation method ignores preprocessing the image, leading to unsatisfactory image segmentation. Based on Prewitt algorithm, a method to optimize the multi-threshold interactive image segmentation was proposed. Firstly, this method used an adaptive algorithm to denoise images and process image textures, and enhanced these images. And then, we interactively processed the enhanced images. In other words, these images were marked and merged in order to improve the segmentation effect. Finally, the threshold selection was optimized through Prewitt algorithm. After the image segmentation, the optimization of multi-threshold interactive image segmentation was achieved. Experimental results show that the proposed method has good effect and performance of image segmentation. And this method has high application value.