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计算机视觉技术在水果品质检测中的研究进展 总被引：3，自引：0，他引：3
水果的品质检测是水果分级的重要依据。随着计算机和图像处理技术的发展、计算机硬件成本的下降和性能的提升,计算机视觉检测技术在水果品质检测方面获得了越来越多的应用。为了能充分利用最新研究成果,该文从计算机视觉技术在水果外观品质和内部品质的检测两个方面,分别综述了国内外的研究进展,并对其发展方向进行了展望,以供我国研究人员做同类研究时参考。 相似文献
2.
随着国家大力发展智慧农业,计算机视觉技术在农业领域中的应用也得到快速发展,推进着农业生产向高质量、高产量的方向不断发展。本文分析了当前计算机视觉在农业领域中农作物病虫害识别、种子和果实分级检测、农作物生长环境监测和农田土壤特征分析等方面的研究现状,并进一步讨论了计算机视觉和深度学习结在农业领域中和应用,最后对计算机视觉技术在农业领域的研究中存在的问题进行了分析和展望。 相似文献
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研究旨在利用具有时空特征的元胞自动机动力学模型对高压脉冲电场处理的果蔬介质进行仿真,模拟果蔬介质计算过程,为高压脉冲电场技术在果蔬保鲜、干燥以及杀菌中的应用提供理论依据。在考虑高压脉冲电场处理果蔬产生细胞电击穿现象以及电击穿原理的基础上,通过元胞空间、状态和规则的制定,构建了元胞自动机果蔬介质击穿模型。结果表明,该试验的模拟结果符合高压脉冲处理果蔬介质的击穿特征,与实际情况对比拟合度高,误差较小。利用元胞自动机仿真高压脉冲电场处理果蔬介质模型,反映了果蔬介质的击穿过程,有利于高压脉冲电场技术在果蔬领域的应用及推广。 相似文献
4.
近红外光谱在果蔬检测中的应用及研究进展 总被引：1，自引：1，他引：0
对近红外光谱在果蔬成分测定和品质分析中的研究近况进行了综述,简单介绍了近红外光谱的基本原理,以及近红外光谱的统计学分析方法和现代检测技术等,并对其最新研究进行了展望。 相似文献
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深度学习在苹果产业链中的应用与研究进展 总被引：1，自引：0，他引：1
我国是苹果生产大国，苹果种植面积广、品种多。将深度学习与机器视觉技术相结合并运用于苹果种植和生产的全产业链中是苹果产业技术升级的重要手段和方向。聚焦苹果产业链中的果树种植、收获采摘和产后检测3个关键阶段，系统性梳理深度学习技术的相关应用与研究进展，其中主要涉及叶部病虫害识别、种植监测、采摘机器人的目标识别和苹果无损分级检测等研究领域，在分析对比不同技术之间的差异与共性的基础上，探讨深度学习在苹果产业链中所面临的困难与挑战。 相似文献
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目前苹果分级自动化程度较低,为了实现苹果品质自动、快速、准确分级设计了一套苹果智能在线检测分级系统。以寒富苹果为测试对象,采用机器视觉技术对苹果分级进行研究。采用阈值分割的方法分割苹果正面图像,逐像素遍历法提取苹果外部轮廓,通过计算其各点到重心的距离提取苹果大小特征,同时计算苹果横径与纵径比提取果形特征。采用支持向量机方法分割侧面苹果图像,计算苹果红色像素占苹果像素的比例提取颜色特征,利用Fisher统计识别的方法提取苹果缺陷。实现了整个分级系统的硬件搭建以及软件的功能,利用该系统对400个苹果样本进行了分级试验,结果表明该系统分级的苹果总体正确率达到95%。设计的基于机器视觉的苹果智能在线检测分级系统克服了传统分级方法的不足,加快了苹果品质分级自动化速度,对水果品质分级等领域有重要研究意义。 相似文献
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用人工神经网络进行果实颜色分级技术研究 总被引：2，自引：0，他引：2
以计算机视觉自动检测果实表面着色度并进行分级为目的,在分析果实表面颜色色相分布特性的基础上,提出将果实色相分布曲线作为模式处理,用人工神经网络进行果实表面颜色分级。结果表明,人工神经网络分级与人工分级的一致度在９４％以上。 相似文献
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Detecting fruits in natural scenes by using spatial-frequency based texture analysis and multiview geometry 总被引：2，自引：0，他引：2
This paper describes a computer vision based model for object detection that can serve as a preliminary step in fruit prognosis, which involves the estimation of the number, diameter and yield of apple fruits. In order to overcome the recognition unreliability in uncontrolled environments caused by uneven illumination conditions, partly occluded surfaces, and similar background features, we rely on a combination of the object's colour, texture and 3D shape properties. In our research, we apply colour segmentation to multiple scene snapshots to separate potential regions from the background and verify them first with texture analysis and second by reconstructing them to 3D space. By analysing all three distinct features (colour, texture and 3D shape) of possible areas, we can safely conclude if they represent fruits we are looking for. Once we detect and verify all areas representing fruits, we can measure their size and model estimated fruit yield. 相似文献
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冬枣果实物理参数与生物特性研究 总被引：1，自引：1，他引：0
为确定冬枣的机械选择性收获参数,试验测定不同成熟度果实的物理及生物特性参数,对其物理及生物特性参数之间的关系进行研究。结果表明:未熟期、白熟期和脆熟期的冬枣果实密度分别为902.15、911.68和947.06kg/m3,硬度分别为17.26、16.24和13.9kg/cm2,果实成熟度越高果实密度越大而果实硬度越小,脆熟期果实的密度及硬度与白熟期和未熟期果实的密度及硬度都存在显著性差异;未熟期、白熟期和脆熟期果实的树枝与果柄分离力都大于果实与果柄分离力,在机械振动收获时,果实脱落发生在果实与果柄连接处,分离力都随着成熟度的增加而减小,白熟期和脆熟期果实的果实与果柄分离力存在显著性差异,有望实现选择性收获;白熟期和脆熟期果实的压缩曲线趋势相似,都没有明显的生物屈服点。白熟期果实的破裂力为145.77N显著大于脆熟期果实的破裂力128.95N,果实和脆熟果实的压缩弹性模量均值分别为2.09和1.89 MPa,二者无显著性差异。果实破裂前,果实所受压力与变形呈近似线性关系。 相似文献
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苹果在线分级系统设计与试验 总被引：1，自引：0，他引：1
【目的】根据苹果采摘机器人结构和作业特点设计与其配套的在线分级系统,满足实时分级需求。【方法】通过预分级机构剔除果径在等级外的苹果,减少视觉分级的无用功;利用力传感器获取苹果质量信息并确定质量等级;通过机器视觉技术实现苹果大小和腐烂面积的检测;借助Matlab和VS2008开发图像处理算法和界面控制程序;构建基于CAN总线的分布式控制网络。对苹果进行综合分级试验。【结果】苹果实际直径与检测直径的决定系数为0.990 3,实际质量与检测质量的决定系数为0.999 6,实际腐烂面积与检测腐烂面积的决定系数为0.985 5,综合分级成功率可以达到89.71%,连续分级时单果平均分级时间为2.89 s。【结论】该分级系统工作稳定,方便扩展,有较高的分级效率和分级精度,可以满足采摘机器人的实时分级需求。 相似文献
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计算机视觉技术已经广泛应用于农业生产领域。对计算机视觉技术在玉米种子质量检验、玉米品种的识别、玉米粒形的检测、玉米田间杂草的识别等方面的应用做了介绍。 相似文献
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城市果蔬垃圾处理现状及再利用对策 总被引：1，自引：0，他引：1
介绍了果蔬垃圾的特性,阐述了城市果蔬垃圾的处理方式,包括焚烧、好氧堆肥、卫生填埋、厌氧消化、固体发酵、生产饲料蛋白。鉴于几种果蔬垃圾处理方式的优点和不足,单一的堆肥化处理、厌氧发酵或固体发酵生产饲料蛋白处理不符合城市果蔬垃圾处理需要的现实情况,设计了一套以厌氧发酵、好氧堆肥和固体发酵生产饲料蛋白技术处理果蔬垃圾系统,该系统在实际使用过程中对果蔬垃圾减量化等作用显著。 相似文献
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A fast normalized cross correlation (FNCC) based machine vision algorithm was proposed in this study to develop a method for detecting and counting immature green citrus fruit using outdoor colour images toward the development of an early yield mapping system. As a template matching method, FNCC was used to detect potential fruit areas in the image, which was the very basis for subsequent false positive removal. Multiple features, including colour, shape and texture features, were combined in this algorithm to remove false positives. Circular Hough transform (CHT) was used to detect circles from images after background removal based on colour components. After building disks centred in centroids resulted from both FNCC and CHT, the detection results were merged based on the size and Euclidian distance of the intersection areas of the disks from these two methods. Finally, the number of fruit was determined after false positive removal using texture features. For a validation dataset of 59 images, 84.4 % of the fruits were successfully detected, which indicated the potential of the proposed method toward the development of an early yield mapping system. 相似文献
15.
Computer vision technology is a sophisticated inspection technology that is in common use in various industries. However, it is not as widely used in aquaculture. Application of computer vision technologies in aquaculture, the scope of the present review, is very challenging. The inspected subjects are sensitive, easily stressed and free to move in an environment in which lighting, visibility and stability are generally not controllable, and the sensors must operate underwater or in a wet environment. The review describes the state of the art and the evolution of computer vision in aquaculture, at all stages of production, from hatcheries to harvest. The review is organized according to inspection tasks that are common to almost all production systems: counting, size measurement and mass estimation, gender detection and quality inspection, species and stock identification, and monitoring of welfare and behavior. The objective of the review is to highlight areas of research and development in the field of computer vision which have made some progress, but have not matured into a useful tool. There are many potential applications for this technology in aquaculture which could be useful for improving product quality or production efficiency. There have been quite a few initiatives in this direction, and a tight collaboration between engineers, fish physiologists and ethologists could contribute to the search for, and development of solutions for the benefit of aquaculture. 相似文献
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A load cell based yield monitoring system was developed for the Oxbo citrus mechanical harvesting machines. The yield monitoring
system consisted of a GPS receiver, a mass flow sensor and data processing and storage units. The mass flow sensor consisted
of four load cells attached to a carbon-fiber plate which sensed the impact force created by the oranges hitting the plate.
A mathematical model was developed to relate the impact force to fruit mass. Laboratory tests were conducted on a test rig
that replicated the flow of oranges to measure the accuracy of the system under a controlled environment. The system performed
very well under laboratory conditions (R
2 = 0.99 and an average error of 3.3%). In addition, a field test was conducted in a citrus orchard in Florida to evaluate
the performance of the system under field conditions. Of the 72 rows used in the field test, the first 10 rows were used to
calibrate the computed weight. A correlation of R
2 = 0.97 between the actual weight and the computed weight was found from the field data with an average error of 7.81%. 相似文献
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脐橙外部品质计算机视觉检测技术初步研究 总被引：6，自引：1，他引：6
根据脐橙图像的特点和分级标准,运用计算机视觉和神经网络算法对脐橙进行自动检测与分级。采用中值滤波和线性低通滤波技术对原始脐橙图像进行平滑、去噪,在对脐橙图像像素点颜色信息统计的基础上,通过设置蓝色分量、色调、饱和度的阈值,从图像中快速准确的分割出果实图像;确定果实横径、果形、表面缺陷率、色泽与着色率为脐橙外部品质分级的特征参数;通过BP神经网络建立了特征参数与脐橙等级之间的关系模型,试验结果表明,其预测准确率达到85％。 相似文献
18.
Detection of immature green citrus fruit is important during the early life cycle of citrus fruit. It allows growers to manage citrus groves more efficiently and maximize yields by identifying expected fruit yields well in advance before harvesting. It also helps the growers prepare harvesting equipment and pickers for the harvesting operation. A novel technique was developed for detecting immature green citrus fruit from an outdoor color image and counting number of fruits. This technique is unique in that it is the first known attempt towards exploring it on green citrus fruits. A set of 71 images containing immature green citrus fruit was acquired in an experimental citrus grove at the University of Florida, Gainesville, Florida, USA. An algorithm was developed using a set of 11 training images by calculating the fast Fourier transform leakage values for fruit and leaves. A threshold value was obtained by comparing the percent leakage of fruit and other objects. The algorithm was tested on a set of 60 validation images. The correct total fruit count for a validation set came out to be 120, whereas the actual number of fruit was 146. The overall correct detection rate was 82.2 %. The proposed algorithm can be further improved to help growers manage their grove more efficiently. 相似文献
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Study of force distribution in the citrus tree canopy during harvest using a continuous canopy shaker 总被引：1，自引：0，他引：1
S.K.J. Udumala SavaryR. Ehsani M. SalyaniM.A. Hebel G.C. Bora 《Computers and Electronics in Agriculture》2011,76(1):51-58
Mechanical harvesting is increasingly being employed in the citrus industry of Florida because of the faster and efficient harvesting it provides with comparatively lower cost when compared to manual harvesting. Continuous canopy shakers are the only mechanical harvesters commercially used in Florida. The main concerns regarding the use of these machines are damage to tree and detrimental effect on next year yield. Because of these concerns, only a very low percentage (6-7%) of the acreage is being harvested mechanically. To improve these machines and address the growers’ concerns, experiments were conducted to study the force and acceleration distribution on the tree branches and fruits. The acceleration was measured at different locations in the canopy using tri-axis accelerometers attached to the branch and data was recorded using ZigBee® transceivers. The distribution of force and acceleration along an individual branch in trees of two different sizes were studied at three different tine angles and frequencies of the shaker. Both distributions were modeled using the Curve Fitting Toolbox™ of Matlab®. The results suggested that the force was higher for the fruits inside the canopy than the ones at the edges. It was also observed that the maximum force required to remove the fruit mechanically was only 18% of the traditionally measured fruit detachment force. The force along the branch was found to be Gaussian in nature and the acceleration along the branch was found to be exponential. 相似文献