基于显微图像处理的稻瘟病菌孢子自动检测与计数方法
稻瘟病菌孢子的检测通常在显微镜下由人工目测完成,该方法费时、费力、自动化程度低。因此,该研究提出了一种基于显微图像处理技术的稻瘟病菌孢子自动检测和计数方法。首先,采用显微图像系统获取稻瘟病菌孢子图像;然后提出一种分块背景提取法对其进行光照校正;根据显微图像中孢子的边缘特征,利用Canny算子进行边缘检测,其中Canny边缘检测过程中的阈值应用模糊C均值算法在梯度图上自动确定;接着对边缘检测后的二值图像进行数学形态学闭开运算处理。根据孢子和主要杂质的形态特征,利用椭圆度、复杂度和最小外接矩形宽度等形态特征参数对目标物进行分类,提取只含孢子的二值图像。最后,提出了基于距离变换和高斯滤波的改进分水岭...
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| Published in | 农业工程学报 Vol. 31; no. 12; pp. 186 - 193 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
华南农业大学工程学院，广州 510642%华南农业大学现代教育技术中心,广州,510642%华南农业大学数学与信息学院,广州,510642%华南农业大学工程学院,广州,510642%广东省农业科学院植物保护研究所,广州,510640
2015
华南农业大学南方农业机械与装备关键技术教育部重点实验室，广州 510642 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2015.12.025 |
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| Summary: | 稻瘟病菌孢子的检测通常在显微镜下由人工目测完成,该方法费时、费力、自动化程度低。因此,该研究提出了一种基于显微图像处理技术的稻瘟病菌孢子自动检测和计数方法。首先,采用显微图像系统获取稻瘟病菌孢子图像;然后提出一种分块背景提取法对其进行光照校正;根据显微图像中孢子的边缘特征,利用Canny算子进行边缘检测,其中Canny边缘检测过程中的阈值应用模糊C均值算法在梯度图上自动确定;接着对边缘检测后的二值图像进行数学形态学闭开运算处理。根据孢子和主要杂质的形态特征,利用椭圆度、复杂度和最小外接矩形宽度等形态特征参数对目标物进行分类,提取只含孢子的二值图像。最后,提出了基于距离变换和高斯滤波的改进分水岭算法对粘连孢子进行分离。测试结果表明：在100幅测试的显微图像样本中,孢子检测的平均准确率为98.5%,满足稻瘟病菌孢子自动检测和计数要求。 |
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| Bibliography: | The detection and counting for spores of the rice blast usually relies on the eye observation under a microscope,which is time consuming,labor intensive and inefficient,so an alternative method is required.This paper discussed an innovative method using image processing techniques to detect and count the spores in micro images.Firstly,the micro images of spores were captured with image detection system consisting of a microscope,a video camera,a capturing software and a computer.And then,a correction method was presented to reduce the non-uniform illumination by subtracting the gray value of the background image form the original image.The original image was divided to 4×4 blocks and the gray value of the background was determined by the illumination correction for each dividing part.The spores had strong edge information in the micro images,so the canny operation was applied to do the edge detection.In this process,fuzzy c-means algorithm（FCM） was used to obtain the high threshold of the canny operation auto |
| ISSN: | 1002-6819 |
| DOI: | 10.11975/j.issn.1002-6819.2015.12.025 |