基于柔性形态变换的图像边缘检测

由于自然界中的噪声影响和图像模糊的边缘,这给图像的边缘检测和目标分割带来了一定的困难。柔性形态变换作为一种数学形态学的方法,既保留了标准形态变换的许多优良特性,又具有较好稳健性,为进行目标特征分析提供了可能。使用柔性形态变换构造边缘检测算子,对图像进行边缘检测。实验结果表明,与其他常用的边缘检测算子相比,基于柔性形态变换的边缘检测算子在有效去噪的同时,能较好地保留图像的细节信息,具有很强的实用性。

Edge detection based on soft morphological transform

With noise in nature and blurred edge of image,edge detection and target segmentation is difficult.As a mathematical morphological method,soft morphological transform has many good characters of standard morphological transform and is robust to noise,so it is possible use it to analyze characters of target.In this paper,we construct edge detector with soft morphological transform and detect blurred edge in image.Experiments show that,it can reserve detail of image and consequently remove noise, comparing with commonly edge detectors.It is very practical to many applications.