基于遗传BP网络的植物根系图像边缘检测  

Edge Detection of Plant Root Images Based on Genetic BP Neural Network

作　　者：宋文龙[1] 郭婧[1] 贾鹤鸣 

机构地区：[1]东北林业大学,哈尔滨150040 [2]哈尔滨工程大学

出　　处：《东北林业大学学报》2011年第12期121-123,共3页Journal of Northeast Forestry University

基　　金：国家自然科学基金项目(30972424);中央高校科研业务费专项基金(DL09CB05)支撑项目

摘　　要：为实现对护坡植被根系图像的轮廓提取和边缘检测,提出一种遗传算法和误差反向传播算法相结合抗噪性强,边缘定位精度高,提取后图像更接近根系真实轮廓图像,更有利于植物固坡研究中根系形态的监测。A hybrid algorithm which combined with genetic algorithm and back-propagation algorithm to train a feed-forward arti- ficial neural network is presented in order to realize the contour extraction and edge detection of the images of plant roots for slope protection. The built eigenvectors for describing the edge are used as input signal of a three-layer feed-forward neural network. The built edge eigenvectors are robust against noise and the genuine information of edge can be extracted effectively in the process of network training. The experimental results illustrate that the designed neural network achieves excellent performance. It is noise robust and accurate in genuine edge positioning. The contour extracted by this method is closer to the practical contour; therefore it is more beneficial to the monitoring of root morphology of vegetations for slope protection research.

关 键 词：植物根系 边缘检测 边缘特征量 遗传BP神经网络 

分 类 号：S718[农业科学—林学] TP183[自动化与计算机技术—控制理论与控制工程]