基于机器视觉技术的血鹦鹉鱼外形评价研究
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摘要
血鹦鹉鱼的外形是分级的重要因素,分级结果决定其市场价值。目前,血鹦鹉鱼分级主要依靠人工进行,主观性强、效率低。本文介绍了利用机器视觉技术对鹦鹉鱼外形评价的方法,详细阐述了在养殖水体不变的情况下,通过Matlab2017a软件控制摄像头完成图片的采集,并通过二值化、取阈值、去噪声、寻找边界等方法对采集到的图像进行处理的过程,最后介绍了利用metric函数判断鱼体边界所围成的闭合曲线是否趋近于圆形,进而完成血鹦鹉鱼外形评价的方法。试验结果表明,该方法能自动完成血鹦鹉鱼的分级,解决传统方法存在的效率低、误差大等问题。
The appearance of red parrot fish is an important factor of grading, and the grading results determine its market value.At present, the classification of blood parrot fish mainly relies on artificial, with strong subjectivity and low efficiency. This paper introduced the use of machine vision technology to evaluate the parrot fish appearance by detailed elaboration under the invariable condition of aquaculture water, through Matlab2017 a camera image acquisition software control, and through the binarization, threshold, de-noising, finding the boundary, processing the collected image, finally introducing the use of metric function to judge whether the fish boundary of closed curve is tend to be rounded so as to complete blood parrot fish shape evaluation. The experimental results showed that this method can automatically complete the classification of blood parrot fish and solve the problem of low efficiency and large error existing in traditional methods.
The appearance of red parrot fish is an important factor of grading, and the grading results determine its market value.At present, the classification of blood parrot fish mainly relies on artificial, with strong subjectivity and low efficiency. This paper introduced the use of machine vision technology to evaluate the parrot fish appearance by detailed elaboration under the invariable condition of aquaculture water, through Matlab2017 a camera image acquisition software control, and through the binarization, threshold, de-noising, finding the boundary, processing the collected image, finally introducing the use of metric function to judge whether the fish boundary of closed curve is tend to be rounded so as to complete blood parrot fish shape evaluation. The experimental results showed that this method can automatically complete the classification of blood parrot fish and solve the problem of low efficiency and large error existing in traditional methods.
引文
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[2]徐愫,邢克智,田云臣.不同光照强度对点带石斑鱼图像分割结果影响的研究[J].天津农学院学报,2016,23(1):34-37,50.
[3]张志强,牛智有,赵思明.基于机器视觉技术的淡水鱼品种识别[J].农业工程学报,2011,27(11):388-392.
[4]李贤,范良忠,刘子毅,等.基于计算机视觉的大菱鲆对背景色选择习性研究[J].农业工程学报,2012,28(10):189-193.
[5]曹晨晨,李光.基于机器视觉的图像形状特征提取方法研究进展[J].包装学报,2015(1):54-60.
[6]杨仁民,郑洲,陈斌,等.基于机器视觉的零件特征尺寸提取算法[J].包装工程,2017(9):151-156.
[7]乔玲玲,毛晓菊.基于改进遗传算法的图像边缘特征提取[J].计算机与数字工程,2016(7):1353-1356.
[8]谢静,庹先国,方晓.基于边缘几何不变性的特征提取算法研究[J].电子技术应用,2015(3):161-164.