利用阈值算法计算二维纳米图像中粒子投影面积的方法

Q3 Mathematics
G. S. Baydin, A. S. Titov
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引用次数: 0

摘要

随着纳米图像研究和实验处理结果网格化的日益复杂,有必要实现这一过程的自动化,以提高所得结果的准确性和可靠性。作为正在进行的研究的一部分,开发了一种自动确定电子显微镜图像中颗粒面积的方法。将阈值算法及其改进方法用于纳米尺度图像中的粒子识别。采用分块匹配和三维滤波算法进行预处理。为了解决这一问题,给出了上述算法在图像应用中的最优序列。考虑了几种阈值算法和相应阈值的计算方法,形成了在所要解决的问题上下文中选择最合适算法的基础。上述方法确定了每个给定图像中粒子数量与其面积的依赖关系。目前,积累了相当大且不断增长的纳米级图像量,这导致需要自动化研究过程。该方法旨在解决在纳米尺度图像中确定粒子面积的实际问题,并可用于实验的各个阶段
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method for Calculating the Particle Projection Area in Two-Dimensional Nanoscale Images using the Threshold Algorithms
The growing complexity of studying nanoscale images and meshing the results of experiments processing makes it necessary to automate this process to improve accuracy and reliability of the results obtained. As part of the ongoing research, a method was developed to determine automatically the particles area in the electron microscope images. The threshold algorithm and its modification was considered to identify particles in the nanoscale images. Block matching and 3D filtering algorithm was selected for preprocessing. The optimal sequence of the above algorithms for images application was obtained in order to solve the problem. Several threshold algorithms and methods for calculating the corresponding threshold values were considered forming the base to select the most appropriate algorithms in the context of the problem being solved. The above method resulted in determining dependence of the particles number on their area for each given image. Currently, quite large and constantly growing volumes of nanoscale images were accumulated, which leads to a need to automate the research process. The proposed method is intended to solve practical problems in determining the particles area in the nanoscale images and could be used at various stages of the experiment
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来源期刊
CiteScore
1.10
自引率
0.00%
发文量
40
期刊介绍: The journal is aimed at publishing most significant results of fundamental and applied studies and developments performed at research and industrial institutions in the following trends (ASJC code): 2600 Mathematics 2200 Engineering 3100 Physics and Astronomy 1600 Chemistry 1700 Computer Science.
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