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The fuel cell components segmentation and visualization based on CT image

机译:基于CT图像的燃料电池成分分割与可视化

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This paper focuses on the image segmentation and three-dimensional visualization based on the CT images of fuel cell. According to the analysis of a variety of traditional edge detection algorithms, Sobel operator and Canny operator are more appropriate on edge detection of the fuel cell tomographic images, and the results of applying them on edge detection of the images are also compared. By analyzing the characteristics of the fuel cell tomographic image grayscale of a particular environment and improving Canny operator, a new method ---- image segementation algorithm for edge detection based on multi-threshold, is designed and implemented, which is also used on two-dimensional image segmentation. Additionally, in order to facilitate a more intuitive observing the fuel cell internal components, this article uses Ray Casting, a commonly used direct volume rendering algorithm of three-dimensional visualization, to rebuild the fuel cell, and applies the multi-threshold image segmentation method on the three-dimensional images to distinguish display the components of liquid water an gas.
机译:本文重点研究基于燃料电池CT图像的图像分割和三维可视化。根据对各种传统边缘检测算法的分析,Sobel算子和Canny算子更适合于燃料电池断层图像的边缘检测,并比较了将其应用于图像边缘检测的结果。通过分析特定环境下燃料电池断层图像灰度特性并改进Canny算子,设计并实现了一种基于多阈值的边缘检测新方法----图像分割算法,该方法在两个方面都得到了应用。维图像分割。此外,为了便于更直观地观察燃料电池的内部组件,本文使用了常用的三维可视化直接体积渲染算法Ray Casting来重建燃料电池,并应用了多阈值图像分割方法在三维图像上区分显示液态水和气体的成分。

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