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# 数学代写|图像处理Digital image processing代考|ELEC4630 A Tool for Science and Technique

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## 数学代写|图像处理代写Digital image processing代考|A Tool for Science and Technique

From the beginning of science, visual observation has played a major role. At that time, the only way to document the results of an experiment was by verbal description and manual drawings. The next major step was the invention of photography which enabled results to be documented objectively. Three prominent examples of scientific applications of photography are astronomy, photogrammetry, and particle physics. Astronomers were able to measure positions and magnitudes of stars and photogrammeters produced topographic maps from aerial images. Searching through countless images from hydrogen bubble chambers led to the discovery of many elementary particles in physics. These manual evaluation procedures, however, were time consuming. Some semi- or even fully automated optomechanical devices were designed. However, they were adapted to a single specific purpose. This is why quantitative evaluation of images did not find widespread application at that time. Generally, images were only used for documentation, qualitative description, and illustration of the phenomena observed.

Nowadays, we are in the middle of a second revolution sparked by the rapid progress in video and computer technology. Personal computers and workstations have become powerful enough to process image data. As a result, multimedia software and hardware is becoming standard for the handling of images, image sequences, and even 3-D visualization. The technology is now available to any scientist or engineer. In consequence, image processing has expanded and is further rapidly expanding from a few specialized applications into a standard scientific tool. Image processing techniques are now applied to virtually all the natural sciences and technical disciplines.

A simple example clearly demonstrates the power of visual information. Imagine you had the task of writing an article about a new technical system, for example, a new type of solar power plant. It would take an enormous effort to describe the system if you could not include images and technical drawings. The reader of your imageless article would also have a frustrating experience. He or she would spend a lot of time trying to figure out how the new solar power plant worked and might end up with only a poor picture of what it looked like.

Technical drawings and photographs of the solar power plant would be of enormous help for readers of your article. They would immediately have an idea of the plant and could study details in the drawings and photographs which were not described in the text, but which caught their attention. Pictorial information provides much more detail, a fact which can be precisely summarized by the saying that “a picture is worth a thousand words”. Another observation is of interest. If the reader later heard of the new solar plant, he or she could easily recall what it looked like, the object “solar plant” being instantly associated with an image.

## 数学代写|图像处理代写Digital image processing代考|Counting and Gauging

A classic task for digital image processing is counting particles and measuring their size distribution. Figure $1.1$ shows three examples with very different particles: gas bubbles submerged by breaking waves, soap bubbles, and pigment particles. The first challenge with tasks like this is to find an imaging and illumination setup that is well adapted to the measuring problem. The bubble images in Fig. 1.1a are visualized by a telecentric illumination and imaging system. With this setup, the principle rays are parallel to the optical axis. Therefore the size of the imaged bubbles does not depend on their distance. The sampling volume for concentration measurements is determined by estimating the degree of blurring in the bubbles.

It is much more difficult to measure the shape of the soap bubbles shown in Fig. 1.1b, because they are transparent. Therefore, deeper lying bubbles superimpose the image of the bubbles in the front layer. Moreover, the bubbles show deviations from a circular shape so that suitable parameters must be found to describe their shape.

A third application is the measurement of the size distribution of color pigment particles. This significantly influences the quality and properties of paint. Thus, the measurement of the distribution is an important quality control task. The image in Fig. 1.1c taken with a transmission electron microscope shows the challenge of this image processing task. The particles tend to cluster. Consequently, these clusters have to be identified, and – if possible – to be separated in order not to bias the determination of the size distribution.

Almost any product we use nowadays has been checked for defects by an automatic visual inspection system. One class of tasks includes the checking of correct sizes and positions. Some example images are shown in Fig. 1.2. Here the position, diameter, and roundness of the holes is checked. Figure $1.2$ c illustrates that it is not easy to illuminate metallic parts. The edge of the hole on the left is partly bright and thus it is more difficult to detect and to measure the holes correctly.

## Matlab代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。