Multimorphological top-hat-based multiscale target classification algorithm for real-time image processing

Chen Zhenzhen; Xing Fei; You Zheng; Wei Minsong; Zhan Haiyang

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Multimorphological top-hat-based multiscale target classification algorithm for real-time image processing

机译：基于多态性的顶帽的多尺度目标分类算法，用于实时图像处理

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The traditional top-hat method is a commonly used method that quickly separates targets from a background. It is used for its fast processing speed and wide range of applications on programmable hardware. However, in some important fields such as microfluidic control, medicine, aerospace, and optical measurement, the observed targets are often spotted with different sizes. The formation mechanism of multiscale spots varies from each other so that they can not be successfully extracted and classified by the traditional top-hat method. To ensure the integrity of targets with a specific size and suppressed noise, the imaging mechanism of different types of spots are studied, and an improved top-hat method with a gray-scale value-based transform is proposed. Compared with the traditional top-hat method, the proposed algorithm is more effective in completely removing unwanted spots. The calculated results of the simulated and real images verify the effectiveness of the double top-hat method in extracting targets with a specific size. Additionally, the resolution of this method is up to the parameter k, which has been discussed in this paper. Furthermore, a multi-top-hat algorithm is presented to distinguish spots of different sizes, and it could be used for real-time multiscale target detection and tracking, as well as real-time multiscale target detection and tracking. (C) 2019 Optical Society of America

机译：传统的顶级帽子方法是一种常用的方法，可快速将目标与背景分开。它用于可编程硬件上的快速处理速度和广泛的应用。然而，在微流体控制，医学，航空航天和光学测量的一些重要领域，观察到的目标通常用不同的尺寸被察觉。多尺度斑点的形成机制彼此不同，因此不能通过传统的顶帽方法成功提取和分类。为了确保具有特定尺寸和抑制噪声的目标的完整性，研究了不同类型的斑点的成像机制，提出了一种改进的基于灰度值的变换的顶帽方法。与传统的顶帽方法相比，所提出的算法在完全除去不需要的斑点方面更有效。模拟和实图像的计算结果验证了双层帽子方法在用特定尺寸提取目标方面的有效性。另外，该方法的分辨率达到了本文已经讨论的参数k。此外，提出了一种多顶帽算法以区分不同尺寸的斑点，并且它可用于实时多尺度目标检测和跟踪，以及实时多尺度目标检测和跟踪。（c）2019年光学学会

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来源
《Applied optics》 |2019年第22期|共12页
作者
Chen Zhenzhen; Xing Fei; You Zheng; Wei Minsong; Zhan Haiyang;
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Tsinghua Univ Dept Precis Instrument Beijing 10084 Peoples R China;

Tsinghua Univ Dept Precis Instrument Beijing 10084 Peoples R China;

Tsinghua Univ Dept Precis Instrument Beijing 10084 Peoples R China;

Tsinghua Univ Dept Precis Instrument Beijing 10084 Peoples R China;

Tsinghua Univ Dept Precis Instrument Beijing 10084 Peoples R China;

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正文语种 eng
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Multimorphological top-hat-based multiscale target classification algorithm for real-time image processing

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