灰飞虱自动识别计数方法研究

doi:10.13733/j.jcam.issn.2095-5553.2024.07.025

摘要/Abstract

摘要： 为更精确地施药，提供可靠的虫量数据，提出一种基于图像识别技术的灰飞虱数量计算方法。设定由拍摄距离和相机调节倍数组成三组拍摄条件，融合区域面积、区域圆度和边界直径三个参数组合构成识别计数模型，利用边缘检测和区域填充完成图像中的个体提取，每组条件下分别计算5张单个长翅和短翅的参数值作为标准。拍摄条件相同的情况下，分别计算4张相互独立和4张有轻微连接的灰飞虱的计数图像，将每个区域的结果比对参数标准值范围，如果三个参数均在范围内，则输出1；至少有一个参数不符合，重新计算该区域面积和边界直径，当同时符合标准值的2倍时，输出2。试验结果表明：灰飞虱全为独立的图像中，有8张相对错误率为0%，3张小于10%，1张为13.3%；轻微连接的图像中，有2张相对错误率为0%，6张小于10%，4张为10%~25%，能满足灰飞虱数量的自动计算。

关键词: 灰飞虱, 自动识别计数, 区域面积, 区域圆度, 边界直径

Abstract: In order to provide reliable insect population data for more accurate application, a method of calculating the number of Laodelphax Striatellus (Fallen) based on image recognition technology was proposed. Three groups of shooting condition were set, which were composed of different shooting distances and camera adjustment factors. A recognition and counting model was formed by the combination of three parameters of the region area, the region roundness and the boundary diameter. The edge detection and region filling were used to complete the extraction of individuals in images, and the parameters values of five single long wing images and five single short wing images were calculated separately in each group condition as standard. Under the same shooting conditions, 4 independent and 4 slightly connected Laodelphax Striatellus (Fallen) count images were calculated respectively, and the results of each region were compared with the standard value range of parameters. If the three parameters were all within the range, 1 was output; If at least one parameter did not match, recalculate the area of the region and the boundary diameter, and output 2 when it met 2 times the standard value at the same time. The results showed that 8 of the independent images had a relative error rate of 0%, 3 were less than 10%, and 1 was 13.3%. Among the slightly connected images, the relative error rate of 2 was 0%, 6 was less than 10%, and 4 was 10%-25%, which could satisfy the automatic calculation of the number of Laodelphax Striatellus (Fallen).

Key words: Laodelphax Striatellus (Fallen), automatic recognition and counting, region area, region roundness, boundary diameter

中图分类号:

TP391.4
S43

程麒文, 邱白晶. 灰飞虱自动识别计数方法研究[J]. 中国农机化学报, 2024, 45(7): 166-171.

Cheng Qiwen, Qiu Baijing. Study on automatic identification and counting method for Laodelphax Striatellus (Fallen)[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(7): 166-171.

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