基于BP神经网络的混凝土超声CT图像分割

由于图像直观的特点，超声波层析成像技术在混凝土结构的无损检测中扮演日益重要的角色。采用BP神经网络模型，研究了超声波CT彩色图像的分割方法。以超声CT检测图像和起导师信号作用的二值图像为训练样本，采用BP算法进行训练，对实测图像分割后得到了目标边缘清晰的较好分割效果：此方法主要优点是设计简单，易于实现；欠缺是BP网络学习时间过长，

A Segmentation Method of Ultrasonic CT Image Based on BP Neural Network

In this paper,the BP neural network method for segmenting the target and detecting the edge from the color image was studied.The samples and their corresponding binary images for BP neural network training were derived from the ultrasonic CT images in concrete's non-destructive detecting.The experimental results showed that the segmentation and the edge detecting effects of the BP network method were satisfying.Easy to design was the best advantage of such method.However the drawback was BP neural network need too much time for learning.