基于最小外接圆直径的苹果分级研究

苹果大小是苹果品质分级的重要因素之一,为实现苹果的大小分级,针对苹果外形近似球的特点,专门设计了一套基于图像处理的苹果大小分选系统。研究采用30个果径为65~95 mm的苹果,模拟苹果在输送翻转装置上的多种随机姿态,对每个试验样本进行9个不同角度的拍摄,将拍摄的所有图像传送给计算机进行二值化、去噪去斑及边缘处理等预处理,提取苹果果径面图像。根据图像边缘确定苹果的质心,寻求质心与边缘的最远距离则为苹果图像的最小外接圆半径;寻求9个图像中苹果的像素面积与其最小外接圆面积最接近的图像,计算出苹果样本果径面的最小外接圆直径。将苹果的实际大小与系统测量大小进行比较,试验表明,研究分选的正确率为96.67%,为苹果大小自动分选提供参考。     

基于高光谱技术的苹果损伤检测装置设计

以苹果为研究对象,基于高光谱成像技术对苹果的机械损伤进行检测,设计了以挑选出的529 nm、622 nm和970 nm这3种波长的点光源半导体激光器作为光源,实时采集3种波长下的苹果图像,并检测标记损伤区域的采集检测装置。系统使用SVM分类算法,利用Matlab GUI制作图像检测界面,判断拍摄区域是否存在损伤,并将判断为损伤的区域标记到苹果图像中。本采集检测装置可以实现3种波长下图像的自动采集和保存,并能基本完成苹果损伤的初步检测。     

糙米储藏过程的品质变化与米粒图像颜色特征参数的关联

通过测定不同储藏温度条件下的糙米脂肪酸值,同时用扫描仪采集糙米图像并基于计算机图像处理方法提取图像颜色特征,考察了储藏过程糙米的表面颜色特征参数的变化及其与脂肪酸值的关联.结果表明:用图像处理方法可以检测出糙米储藏过程米粒表面颜色的变化;糙米表面的亮度值随着储藏时间延长和储藏温度提高而增大的趋势最明显;糙米储藏过程的亮度值变化与脂肪酸值增加的趋势基本一致,全部糙米试样两者的相关系数为r=0.81,具有较强的关联性,提示了用图像处理方法及用米粒颜色特征参数表征糙米储藏过程品质变化的有效性和可能性.     

基于最小外接矩形的牛角椒大小分级研究

为实现用机器取代人工对牛角椒进行大小分级,针对牛角椒的外形近似弧的特点,设计一个基于图像处理的牛角椒大小分选系统。研究选取100个某一品种的牛角椒,首先对牛角椒进行拍摄,然后将拍摄的图像进行图像预处理,提取辣椒边缘,并去除辣椒柄,最后对去柄后的边缘通过最小外接矩形的方法得到矩形的4个顶点坐标,再选取1个牛角椒中点,计算出牛角椒的弧形长度。将牛角椒的系统检测大小与实际大小进行比较,系统检测的辣椒分级正确率为95%,研究结果为牛角椒大小自动分级提供了参考。     

基于MATLAB图像处理的大豆颗粒检测方法研究

为解决大豆单株考种过程中人力计数准确率低和数粒仪等光电方法耗时长等问题,采用计算机视觉系统及MATLAB软件开发平台代替人工大豆单株考种进行自动检测的方法。该算法采用对大豆颗粒图像进行空间滤波去除噪声及“Otsu”方法对图像进行最佳全局阈值分割处理,在对图像处理的基础上完成对大豆颗粒个数、颗粒大小两项指标的测定。以六个大豆品种周黑豆、周青豆、周豆11、周豆18、周豆22和周豆23的籽粒为试验对象,探究大豆颗粒计数、大豆颗粒大小分级两项指标的确定。实验结果表明：该算法及程序准确有效,能准确计算大豆单株颗粒个数;该算法及程序判断出的各品种大豆颗粒平均面积大小与百粒重成正相关,且决定系数为0.9141,即可得该算法及程序可准确有效的判断大豆颗粒大小。总之,基于MTALAB图像处理大豆单株颗粒检测方法的研究可相对减轻人力劳动强度及人类视觉的不足,在提高工作效率和准确度等方面有重要意义。     

基于高光谱图像技术的水果表面农药残留检测观察

水果品质检测对水果的生产以及销售十分关键。光谱技术具备操作简便、非破坏、高精准、高效的特征,在农药残留中获得了显著的应用。通过高光谱图像技术而检测在水果表面的农药残留情况,可以使百姓食用到真正放心的水果。     

融合马尔可夫随机场与量子粒子群聚类的棉花图像分割算法

【目的】提高采摘机器人棉花图像处理系统中的图像分割准确率。【方法】提出融合马尔可夫随机场与量子粒子群聚类的图像分割算法。步骤:将读入的RGB模式彩色图像转换成灰度图像;利用本算法分割图像;通过对连通区域面积阈值的设定获取目标区域。使用本算法分割不同角度采集的棉花正面图像与棉花侧面图像,并采用分割精度、峰值信噪比,分别与Otsu算法、模糊聚类图像分割算法、量子粒子群图像分割算法和马尔可夫随机场图像分割算法进行效果比较。【结果】本算法分割精度、峰值信噪比平均值分别为98.94%、77.48dB,与Otsu算法、模糊聚类图像分割算法、量子粒子群图像分割算法、马尔科夫随机场图像分割算法相比,分割精度、峰值信噪比分别提高2.47~4.56百分点、9.81~13.11 dB。【结论】本算法处理棉花图像具有更高的分割精度以及峰值信噪比。     

基于Visual c++矩形标尺智能识别

通过利用图像处理和图像识别领域的边界分割Robert局部边缘检测算子方法及梯度算子区域迭代的阈值图像分割算法相结合来对图像特征进行二次提取,不同于单独采用边界分割与区域分割算法,该算法通过对边缘检测结果的差分结果的迭代分析,有效的增强了识别算法对识别条件的适应性及识别精度,并采用Visual C 编程进行计算机图像辅助设计作为实现手段.     

MATLAB在储粮害虫图像处理中的应用

在对粮虫图像处理过程中,介绍了Matlab图像处理工具箱中的函数,实现了图像处理与分析的技术,边缘检测及轮廓提取,通过形态学方法进行图像特征抽取与分析,采用小波变换的处理方法去除粮虫图像噪声,达到了比较好的效果。     

基于高光谱成像技术的核桃黑斑识别研究

利用高光谱成像技术对黑斑核桃进行识别研究,采集80个正常核桃和80个黑斑核桃高光谱图像,并提取感兴趣区域获得样本光谱数据。利用主成分分析(Principal component analysis,PCA)提取光谱数据前5个主成分信息,建立PLS判别模型,结果表明模型判别率均为100%。提取5个主成分图像,分别采用掩膜(Mask)、"Canny"算子、图像填充、区域生长算法(Region grow)提取模板图像和黑斑区域,实现对黑斑的识别。研究表明,采用高光谱图像技术可以实现核桃黑斑的识别,为核桃的黑斑检测提供理论参考。     

Key technology of detecting hot heavy rail steel surface faults based on machine vision

Aiming at the low efficiency and precision of hot rail steel surface faults detecting at present,a suit of surface defect detection system of hot heavy rail based on the machine vision is put forward. Multi-CCD cameras are used to collect pictures. According to the geometric characteristics of the heavy rail and its defect characteristics of high-frequency region,six angle shot is used for heavy rail,and then various image processing technology are adopted in workstation. The system adopts improved Hough transform to get surface faults and Kohonen network to make a classification for the characteristics of low SVM training algorithm. The above key machine vision technology for detection of hot heavy rail surface defects greatly improves the speed and accuracy of testing and the detecting correct rate arrives over 85%.     

Novel Image-adaptive Watermarking Algorithm

Digital watermarking is an effective method to provide copyright protection for digital media. A blind image- adaptive watermarking algorithm based on DCT domain is presented. The algorithm selects adaptively the step size of quantization to embed the watermark bits by modifying DC components via the human visual system model and local characteristics of image; at the same time some AC components of the blocks with less perceptual capacity are also modified to embed the same watermark bits by using quantization. Thus the relation between robustness and imperceptibility can be well balanced. The algorithm recovers the watermark without any reference to the original image. Compared with the similar algorithm reported in the literature, this method can give better image quality and is better robust against noise and commonly used image processing techniques.     

A Globally Convergent Algorithm for Nonlinear Programming

A new globally convergent algorithm was presented for a continuous differen-tiable nonlinear programming by defining a measure function deviating from the Kuhn-Tucker point. With this algorithm which can be used to get the optimum solution of the problem,the optimal lagrangian multiplier corresponding the optimal solution of the problem was also obtained. A new iterative algorithm for quadratic programming is obtained when applying the general algorithm to quadratic programming. Finally,a numerical example was given.     

Inheritance of calyx shape in the genus Origanum (Lamiaceae)

Five different traits responsible for calyx shape within the genus Origanum were found to be determined by five independent genes. The five traits are bell‐shaped vs. tubular‐shaped calyx, angular vs. round teeth on the upper lip, entire vs. denticulate upper lip, fully developed vs. reduced lower lip and entire vs. denticulate lower lip. The simple Mendelian inheritance of most traits for calyx shape could be used to identify hybrids between Origanum species arising from open‐pollinated plants and so avoid tedious artificial pollination resulting from small flower sizes in Origanum. Such hybrids are interesting base material for character transfer (e.g. winter hardiness or seed size) between economically important species.     

基于最小阈值法的棉花幼苗识别研究

 面对纯机械式分苗机构经常出现的漏分和多分的问题,本文提出使用基于最小阈值法的图像识别技术对棉花幼苗进行识别和分离。使用了HSV颜色空间内与光照条件无关的H值将RGB真彩色图像转化为灰度图像,以提高图像处理的实时性。基于最小值阈值法,提出一种能够有效地将处于复杂背景下的棉花幼苗茎部图像提取的方法,使用棉花幼苗茎部图像的面积和长宽比等几何信息能有效识别棉花幼苗,并得到棉花幼苗茎部的重心坐标。本文的研究证明了用图像处理中的最小阈值法识别棉花幼苗是可行的。     

A fast image segmentation algorithm with local C V active contour model

For the typical C V Algorithm, there exists the weakness of requiring multi iterative operations and long time computation to deal with large size image. Based on the analysis upon the relationship between the image size and the initialized approaching image with the number of iterations and computing time to obtain the stead results, an improved local C V image divisional algorithm based on the segmentation of threshold value and the connected domain labeled algorithm to deal with large size image is proposed. The OTSU method is used to divide the threshold value of image to reach the goal of label and local segmentation of image through the fast non recursion algorithm of connected domains. The segmented pieces and the result of its segmentation are used as the initialized approaching image of the C V algorithm model. Compared with the classical C V algorithm, the analysis and simulated result indicates that the improved C V algorithm reaches the steady solution quickly with fewer times of iterations. The proposed method can handle large size image with profound contour details quickly and effectively.     

基于粒子群算法和支持向量机的黄花菜叶部病害识别

使用数字图像处理技术,以黄花菜叶部病害图像为识别对象,基于Lab空间和K-means聚类算法分割病害区域,提取目标区域的颜色特征、方向梯度直方图(histogram of oriented gradient,HOG)特征和形状特征,分别建立单一特征模型和特征融合模型,采用粒子群(particle swarm optimization,PSO)算法通过交叉验证优化支持向量机(support vector machine,SVM)模型的惩罚因子和核参数,建立基于PSO-SVM的多特征融合分类模型识别黄花菜病害。基于SVM的多特征融合分类模型识别率高于单一特征分类模型,识别率可达为81.67%;基于PSO-SVM多特征融合分类模型识别率高达92.39%。基于PSO-SVM的多特征分类模型识别率高,可以及时、便捷、高效地识别黄花菜病害。     

陆地棉不同组织器官原花青素含量分析

旨在研究棉花不同组织器官中的原花青素的含量。采用可见分光光度法分别测定棉花品种‘中棉所35’的花萼、叶片、花瓣、茎和根等组织器官中原花青素的含量,比较其在各组织器官中的分布。分析结果表明,可溶性的原花青素在花萼中的含量最高,为0.040μg/mg（新鲜组织）,叶片和花瓣中的含量较高,分别为0.030、0.017μg/mg,而根含量最低,为0.005μg/mg;非可溶性的原花青素含量在各组织器官中的含量与可溶性的分布呈大致相同的趋势,花萼、叶片、花瓣、茎和根含量分别为2.324、1.742、1.449、0.417、0.384μg/mg。在棉花中原花青素主要以非可溶性形式存在,而可溶性的含量较低,在花瓣中两者相差达到84倍,在茎里相差也达到29倍。研究结果暗示原花青素在各组织器官中分布不均衡可能与其执行不同功能有关,与棉花抗、耐逆性有着重要的关系。     

Binary Images Processing Based on Adaptation to Mixture Transform Coding

To enhance quality of image processing, it is demanded that coding algorithm should be simplified and the speed of image processing should be faster,and information loss on image compressed should be minimum.Adaptive segmentation is given for image which to be processed.Region coding is combined with threshold coding.Adaptation to mixture transform coding is fulfilled.Results of simulation shows that with this method coding loss witch images are compressed is mined and quantity of image processing is good.