基于蚁群算法的图像分割方法

Image Segmentation Method Based on Ant Colony Algorithm

为提高图像分割后的清晰度,提出基于蚁群算法的图像分割方法。通过提取图像中的分割特征,构建蚁群搜索过程数据模型,该数据模型主要依靠蚁群多态算法对图像中的灰度值作出计算分析。设置各个蚁群规则,设定初始聚类中心,根据初始聚类中心确定图像分割的路线,确保图像要素提取质量不受影响,实现多态蚁群算法图像分割。通过实验测试,与阈值图像分割法对比,论证该方法的可行性与优越性。

In order to improve the clarity of image segmentation,a research design based on the ant colony algorithm for image segmentation is proposed.By extracting the segmentation features in the image,the ant colony search process data model is constructed.The data model mainly relies on the ant colony polymorphic algorithm.The gray value in the image is calculated and analyzed,each ant colony rule is set,the initial clustering center is set,and the image segmentation route is determined according to the initial clustering center to ensure that the image element extraction quality is not affected,and the polymorphic ant colony algorithm image is realized Segmentation,through experimental tests,compared with the threshold image segmentation method,demonstrates the feasibility and superiority of this method.