查询结果:   孙吉祥,梁敬东.基于图像分割和轮廓矩的果蝇求偶行为识别方法[J].计算机应用与软件,2015,32(4):145 - 148.
中文标题
基于图像分割和轮廓矩的果蝇求偶行为识别方法
发表栏目
人工智能与识别
摘要点击数
1009
英文标题
RECOGNITION OF DROSOPHILA COURTSHIP BEHAVIOUR BASED ON IMAGE SEGMENTATION AND CONTOUR MOMENTS
作 者
孙吉祥 梁敬东 Sun Jixiang Liang Jingdong
作者单位
南京农业大学信息科学技术学院 江苏 南京 210095     
英文单位
College of Information Science and Technology,Nanjing Agricultural University,Nanjing 210095,Jiangsu,China     
关键词
图像分割 轮廓矩 灰度图像 神经网络 果蝇求偶
Keywords
Image segmentation Contour moment Grayscale image Neural network Drosophila courtship
基金项目
国家转基因生物新品种培育重大专项(2009ZX08001-002B);中央高校基本科研业务费专项基金项目(KYZ20 1005)
作者资料
孙吉祥,硕士生,主研领域:数据挖掘,生物信息学。梁敬东,副教授。 。
文章摘要
监控害虫求偶行为是农业病虫害防治的重要手段,传统的人工识别工作量大、效率低下,为实现自动检测与识别果蝇求偶行为,设计了基于图像分割和轮廓矩的识别方法。该方法首先采用基于灰度图像的背景生成、更新和阈值分割的方法自适应地获取果蝇的轮廓。然后根据轮廓矩理论,提取各果蝇轮廓的矩不变量并输入BP神经网络判断是否发生单侧振翅行为。最后根据果蝇间的位置关系,判断振翅果蝇是否在尾随其他果蝇,从而确定其是否发生了求偶行为。采用人工检测的方法进行对比验证,结果表明该方法能够有效地识别果蝇的求偶行为,准确识别率达89.6%。
Abstract
Monitoring pests’ courtship behaviours is a major means in agricultural pest and diseases management. Traditional manual identification has heavy workload and low efficiency. In order to detect and identify the courtship behaviours of drosophilae automatically, we design an identification method which is based on image segmentation and contour moment. First, the method employs the grayscale image-based methods of background generation, update and threshold segmentation to adaptively obtain the contours of drosophila. Then according to the theory of contour moments, it extracts the contour moment invariants of every drosophila contour and inputs them into BP neural network to estimate whether the drosophila vibrates its unilateral wing. In third step, it judges whether or not the wing-vibrating drosophila is trailing other drosophilae according to the position relationship between them so as to determine if drosophila has the courtship behaviour happened. Contrast verification is carried out in manual detection way, results show that the new method can effectively identify the courtship behaviour of drosophila and the accuracy of recognition reaches 89.6%.
下载PDF全文