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MatLAB啤酒中杂质图像识别分析+程序

时间:2021-08-13 19:58来源:毕业论文
为了尽可能的消除拍照设备和周围环境对于采集到的图像所造成的影响,运用图像灰度增强、图像去噪处理等对啤酒图像进行处理,为杂质分析做充分的准备。课题选取边缘检测的方法

摘要:啤酒中杂质的检测在啤酒的合格检测中占有重要的地位,目前多采用人工检测或高效液相色谱技术进行检测。论文运用数字图像处理的原理,利用MatLAB软件的图像处理工具箱对杂质图像进行处理,完成对于光线不足、外界环境干扰、图像变形等不同情况下啤酒溶液中杂质的识别并编程实现。由于图像增强、边缘检测的首要条件是图像为灰度图像,所以首先要将数字图像转换为灰度图像。为了尽可能的消除拍照设备和周围环境对于采集到的图像所造成的影响,运用图像灰度增强、图像去噪处理等对啤酒图像进行处理,为杂质分析做充分的准备。课题选取边缘检测的方法对啤酒中杂质图像进行识别和分析,然后运用检测梯度的最大值的方法实现杂质的检测。70691

毕业论文关键词:液体图像;图像处理;图像增强;边缘检测;杂质检测

Detect and analyse images of impurities in beer

Abstract: The detection of impurities in beer plays is important in the detection of qualification test of beer.At present,those detection is manual work or via High Performance Liquid Chromatography(HPLC) device.This thesis is used the methods and theories of digital image processing technology and with the help the image processing toolbox of the MatLAB software,deal with the images of impurities. Complete for the detection of impurities in beer under different conditions, such as unenough light, distribution, anamorphose, etc. Because the first condition of enhancement of image and edge detection technology is that the image is the cineration one,so digital image should be converted into cineration image.As far as possible eliminate the effect of camera equipment and surrounding environment to the image,using image gray-scale enhancement and image denoising to deal with the image,and making adequate preparations for analyse image.This thesis chooses edge detection technology to detect and analyse images of impurities in beer,and applies the way of testing the maximum gradient to achieve the identification of impurity.

Keywords:liquid image;image processing; image enhancement;boundary detection;impurity detection

目录

摘要 i

Abstract i

目录 iii

1 绪论 1

1.1 课题背景 1

1.2 论文原理及所做工作 2

1.2.1 图像处理的发展 2

1.2.2 图像处理主要内容 2

1.2.3 所做工作 3

1.2.4工作重点 4

2 啤酒杂质识别的数字图像处理原理 5

2.1 数字图像处理技术的基本概念 5

2.2 数字图像处理技术及其处理过程 6

2.2.1 数字图像处理技术的主要特点 6

2.2.2 数字图像处理技术的优点 6

2.2.3 数字图像处理技术的处理过程 7

2.3 图像处理技术的基本方法 MatLAB啤酒中杂质图像识别分析+程序:http://www.youerw.com/tongxin/lunwen_80120.html

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