基于神经网络的树叶识别系统研究

在林业系统注册树木种类时,通常采用大量树叶上的可见外形特点来辨别数目繁多的树木种类。针对此问题,本文提出了基于神经网络的树叶识别方法,该方法建立并管理一个分等级的树叶图像体系,通过对不同种类树叶的边缘提取来识别每种树叶的特征点,从而得到树叶的外部轮廓来区分树木种类:给出了相应的改进型神经网络算法,并给出详细的论述过程:最后,通过Java语言给出了系统实现并做了大量的数值仿真。结果证明本文方法是可行有效的。图4表1参8。

Recognition system of leaf images based on neuronal network

In forest variety registration, visual traits of the plants appearance are widely used to discern different tree species. The new rec- ognition system of leaf image strategy which based on neural network established to administrate a hierarchical list of leaf images, some sorts of edge detection can be performed to identify the individual tokens of every image and the frame of the leaf can be got to differentiate the tree species. An approach based on back-propagation neuronal network is proposed and the programming language for the implementa- tion is also given by using Java. The numerical simulations results have shown that the proposed leaf strategy is effective and feasible.