农业机械学报2017，Vol.48Issue(9)：32-37,6.DOI:10.6041/j.issn.1000-1298.2017.09.004
小波变换与分水岭算法融合的番茄冠层叶片图像分割
Segmentation of Tomato Leaves from Canopy Images by Combination of Wavelet Transform and Watershed Algorithm
摘要
Abstract
In the study of crop nutrition diagnosis based on machine vision,it is usually necessary to collect leaf samples and quantitatively determine their nutrient content under laboratory conditions.However,due to the overlapping of leaves,the leaf samples cannot be clearly reflected in the canopy image.In order to solve this problem,it is needed to use image analysis technology to effectively extract the leaves in the crop canopy image and according to the processing results to collect laboratory test samples.Based on the complex background extraction,gradient graph calculation,wavelet transform,marker selection and watershed segmentation,the leaf segmentation of tomato canopy multispectral image was realized.Firstly,four kinds of complex background elimination algorithms were compared.It was found that the threshold segmentation based on normalized difference vegetation index (NDVI) was accurate when the enhancement factor was 1.3,which was suitable under various lighting conditions,and the space-time complexity was low.Secondly,in the aspect of gradient graph calculation,the morphological gradient of near-infrared (NIR) band image can eliminate the texture of the leaves caused by veins,light and so on while keeping the target edge.Then,markers of leaves were selected according to wavelet transform that used the low-frequency coefficient of 4-level db4 wavelet decomposition and Hmaxima transform with threshold of 18.Finally,the results of wavelet transform watershed segmentation and mathematical morphology watershed segmentation were superimposed,and it was found that the average segmentation error rate of tomato canopy leaves was 21％ for complex background and different light intensities,which provided some technical support for the analysis of tomato leaf nutrient content detection.关键词
图像分割/番茄叶片/小波变换/标记分水岭Key words
image segmentation/tomato leaves/wavelet transform/marked watershed分类
信息技术与安全科学引用本文复制引用
丁永军,张晶晶,LEE Won Suk,李民赞..小波变换与分水岭算法融合的番茄冠层叶片图像分割[J].农业机械学报,2017,48(9):32-37,6.基金项目
国家自然科学基金项目(31360291、31271619)、国家留学基金委西部地区人才培养特别项目(201408625069)和兰州城市学院博士科研启动基金项目(LZCU-BS2013-07) （31360291、31271619）
