Assessing exterior egg quality indicators using machine vision     

A. V. Vasileva  E. V. Gorbunova  A. S. Vasilev  V. S. Peretyagin  A. N. Chertov  V. V. Korotaev 《British poultry science》2018,59(6):636-645

ABSTRACT

1. The objective of this study was to develop a machine vision method for analysing exterior parameters of chicken eggs to automate the stage of primary sorting.

2. The developed algorithm based on predetermined thresholds calculated egg quality indicators, including geometric dimensions, shape index and the mottling grade. The algorithm was implemented with an experimental setup that combined the image-based and the candling methods. A total of 400 egg samples were analysed.

3. Comparison of results of the algorithm with those obtained using the traditional manual method showed that mean value of radii values difference was 0.095 ± 0.058 mm for the sharp and 0.080 ± 0.047 mm for the blunt end of the egg, with standard deviations of 0.58 mm and 0.49 mm, respectively.

4. The correlation coefficient between the shape index values determined by the two methods was 0.93; the standard deviation of absolute differences between corresponding values was 1.05%.

5. The results of mottling grade estimation were compared using F-measure and confusion matrix.

6. The results allow the possibility to perform the assessment of egg exterior quality factors in an automatic mode, independent of the expertise of a grader.  相似文献   

A computer vision system for oocyte counting using images captured by smartphone     

《Aquacultural Engineering》2019

This work proposes a computer vision procedure for counting Twospot astyanax (Astyanax bimaculatus) oocytes in Petri dishes using images captured by smartphone. First, the proposed procedure uses simple linear iterative clustering (SLIC) to divide the images into groups of pixels (superpixels). Then, based on their color and space characteristics, the images are classified into light background, dark background, dirt, or oocyte by a machine learning algorithm. Five different types of machine learning algorithms were tested: support vector machines (SVM), decision trees using the algorithm J48 and random forest, k-nearest neighbors (k-NN), and Naive Bayes. To train the algorithms, 8.578 superpixels were classified by an expert into oocyte (n = 354), dirtiness (n = 651), dark background (n = 3.622), and light background (n = 3.951). Of the five learning algorithms, SVM obtained the best result with 97% correct oocyte recognition. Given the wide availability of smartphones, we therefore conclude that the presented procedure can be a valuable tool in future experiments and studies on fertilization and hatching success in Twospot astyanax.  相似文献   

基于机器视觉的玉米秸秆行实时定位机器人设计     

张丽  胡应占  汪小志  鲍秀兰 《农机化研究》2016,(6):41-45

为了实现机器人玉米秸秆行的精确定位,对耕作玉米机器人的结构进行了改进,并提出了一种基于泰勒级数展开式的RSSI定位方法,提高了机器人玉米秸秆行的定位精度。定位系统使用高清晰度的摄像机采集图像,并采用PID闭环反馈的方式控制机器人的位移,利用PC主控端图像处理,实现了实时定位功能。为了验证机器人玉米秸秆行定位的可靠性,采用田间试验的方法对机器人的性能进行了测试。结果表明:RSSI定位方法的定位精度较高,且图像处理系统可以准确地标定玉米秸秆行,实现机器人在玉米田中的精确定位,避免了机器人在作业过程中对农作物造成损害。  相似文献   

金融时间序列指标判别框架：以特质波动率为例     

汤胤  毛景慧 《湖南农业大学学报(自然科学版)》2016,(3):35-39

基于拐点集合判别的TBUD方法主要思路是分析拐点集合间的关系，并在高维空间进行划分，从而搭建判别模型，并将分析框架应用在特质波动率等若干指标上，利用实证数据得到结论。应用TBUD判别框架可以发现，特质波动率等指标无法对拐点集合进行清晰划分，因而并不具有预测能力。  相似文献   

ASAS-NANP SYMPOSIUM: Applications of machine learning for livestock body weight prediction from digital images     

Zhuoyi Wang  Saeed Shadpour  Esther Chan  Vanessa Rotondo  Katharine M Wood  Dan Tulpan 《Journal of animal science》2021,99(2)

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基于机器视觉的饲料生产智能包装系统设计与应用研究     

侯岩妍 《饲料研究》2021,(3):110-113

为提高饲料生产订单的包装效率、智能化程度、降低包装成本,文章基于机器视觉,从硬件选择与软件设计两个层面设计饲料生产智能包装系统。采用AutoMod软件对饲料生产智能包装系统进行仿真试验,检验整个包装系统效果。结果表明,该智能包装系统包装效率高、关键设备利用率高、系统可靠性、可行性良好。  相似文献   

计算机视觉技术在智慧羊场中的研究进展     

姚州  谭焓  田芳  周勇  章程 《中国饲料》2021,1(7):7-12

智慧羊场具有科学化、标准化管理的优点,是羊场转型发展的趋势。计算机视觉技术是人工智能的核心,可以实现非接触性、自动化、实时监测羊的个体信息。本文总结并分析了计算机视觉在羊场的个体识别方法、行为识别方法、体尺与体重估测、疾病监测的研究现状,并指出计算机视觉在智慧羊场的进一步发展趋势。 [关键词] 计算机视觉|智慧羊场|个体识别|行为识别|体尺与体重估测|疾病监测  相似文献   

Design for Precision Measurement System Based on Machine Vision     

LIAO Qiang  MI Lin  ZHOU Yi  XU Zhong jun 《保鲜与加工》2002,(12):21-23

It is difficult to measure the geometric quantity of small parts in finishing, assembling and measuring, because it's easy to break the workpieces' surface and alter their position by means of traditional contact measuring methods.There are some non contact measurers, such as,light feeler pin and interference microscope etc., because of it's high price and strict working conditions,so it's difficult to promote them in widely use. Precision measurement system based on machine vision has the advantages of non contact measuring as well as high performance and low price. Some problems, such as light source, algorithm of edge fitting, auto focusing,are discussed.  相似文献   

Computer-aided Classification and Identification of Traditional Chinese Medicine Herbal Formula     

CAI Cong-zhong  YUAN Qian-fei  XlAO Han-guang  LIU Xing-hu  KONG Chun-yang 《保鲜与加工》2006,(10):42-46

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Design of Vision System Based on Service Robot     

LIU Jing-cheng  LIAO Zhi-yong  ZHU Mu-jian  LIU Jun 《保鲜与加工》2006,(11):31-35

A vision system based on the service robot is involved. In the system, picture signal is acquired by the picture sensor OV7635. Frame memory AL422B is used as data buffer memory, while CPLD controlled the time order DSP performed. In the software system of image processing, to accomplish color image segmentation and recognition, the threshold vector judgment and improved seed-fill algorithm is introduced, and the image geometric moment is calculated during the segmenting. In order to achieve a vision servo system which composed of image-based feedback and adaptive compensation, the deduced matrix-based Jacobian from the image moment is taken as image feature. Adopted the TFT LCD is adopted to straightly disolav the result of vision recognition and vision tracing.  相似文献