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An Android Application for Plant Identification

机译:用于植物识别的Android应用程序

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This paper presents an Android application to automatically identify plant species using a single leaf image as input. At the pre-processing phase, we proposed an improved segmentation method to eliminate the noise caused by capturing on non-uniform background so we can obtain the binary image which only contains the leaf shape. Then, several morphological features and Hu moment invariants descriptors were extracted as inputs of a joint classifier which combines the back propagation neural network(BPNN) with a weighted k-nearest-neighbor (KNN) to distinguish 220 species of plants. The outputs of the joint classifier are the top ten species that best match the query leaf image. At the end, we implemented these algorithms on Android OS and the application we developed has been downloaded about a million times.
机译:本文介绍了一个Android应用程序,该应用程序使用单个叶子图像作为输入来自动识别植物物种。在预处理阶段,我们提出了一种改进的分割方法,以消除由于在不均匀背景上捕获而产生的噪声,从而可以获得仅包含叶形的二值图像。然后,提取了几个形态特征和胡矩不变性描述符作为联合分类器的输入,该联合分类器将反向传播神经网络(BPNN)与加权k近邻(KNN)结合起来以区分220种植物。联合分类器的输出是最匹配查询叶图像的前十种。最后,我们在Android OS上实现了这些算法,并且我们开发的应用程序已被下载约一百万次。

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