|本期目录/Table of Contents|

[1]罗晓丽.基于Canny算子的柑橘果实病斑信息智能提取方法研究[J].绵阳师范学院学报,2019,(08):95-100.[doi:10.16276/j.cnki.cn51-1670/g.2019.08.018]
 LUO Xiaoli.Study on the Intelligent Extraction Method of Citrus Fruit Smudge Information based on Canny Operator[J].Journal of Mianyang Normal University,2019,(08):95-100.[doi:10.16276/j.cnki.cn51-1670/g.2019.08.018]
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基于Canny算子的柑橘果实病斑信息智能提取方法研究(PDF)
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《绵阳师范学院学报》[ISSN:1672-612X/CN:51-1670/G]

卷:
期数:
2019年08期
页码:
95-100
栏目:
计算机与网络技术
出版日期:
2019-08-20

文章信息/Info

Title:
Study on the Intelligent Extraction Method of Citrus Fruit Smudge Information based on Canny Operator
文章编号:
1672-612X(2019)08-0095-06
作者:
罗晓丽
福州职业技术学院信息技术工程系, 福建福州 350108
Author(s):
LUO Xiaoli
Department of Information technology engineering,Fuzhou Polytechnic, Fuzhou,Fujian 350108
关键词:
阈值分割 Canny算子 连通图像 块状效应
Keywords:
threshold segmentation Canny operator connected graph The massive effect
分类号:
TP311.13
DOI:
10.16276/j.cnki.cn51-1670/g.2019.08.018
文献标志码:
A
摘要:
为实现对病害的及时准确的识别,利用计算机提取病害图像信息方法已成为目前研究的热点。目前主要是采用中值滤波法、双峰法、otsu阈值分割法、贝叶斯判别方法等算法及相关算法的组合算法从颜色特征,形状特征角度提取病斑信息,这些算法大多运算复杂,存储空间大,识别的精度低,无法全面完整提取病斑信息,本文采用一种改进的Canny算子算法来解决上述问题。同时使用MATLAB软件进行仿真,仿真结果显示对于果实病斑识别及提取都能够较好的满足需求.
Abstract:
The diagnosis and prevention of fruit disease spots not only affect the appearance and quality of fruit, but also directly impact on the quality of fruit.Traditional pest detection often delays the diagnosis of disease and miss the best time for application of medicine, due to inaccurate detection or untimely report.For more efficient identification of diseases, the method of extracting disease image information through computer has become a hot research topic.At present, median filtering method, bimodal method, otsu threshold segmentation method, the algorithm and related algorithms are mainly adopted extracting disease spot information through its color feature and shape feature.These algorithms require complex computing and large storage space, and are low efficient in the recognition precision.An improved Canny operator algorithm was presented to solve the above problems.At the same time, MATLAB software was used for simulation, and the simulation results showed that the identification and extraction of fruit disease spots could better meet the requirements.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-02-10
基金项目:福建省教育厅科技项目(JAT160819)项; 福州职业技术学院校级科研项目(FZYKJJJC201802).
作者简介:罗晓丽(1971- ),女,黑龙江五常人,副教授,工程硕士,研究方向:图像计算研究.
更新日期/Last Update: 2019-08-20