中文摘要：

在森林变化登记，植物外观的视觉特点广泛地被用来认出不同的树种类。基于神经网络建立了管理叶的一张层次表的叶图象策略的新识别系统想象，某种边察觉能被执行识别每幅图象的单个标志；叶的框架能被开始区分树种类。一条途径基于背繁殖 neuronal 网络被建议；为实现的程序语言被使用 Java 也给。数字模拟结果证明了建议的叶策略是有效的；可行。

英文摘要：

In forest variety registration, visual traits of the plants appearance are widely used to discern different tree species. The new recognition 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 implementation is also Riven by using Java. The numerical simulations results have shown that the proposed leaf strategt is effective and feasible.