Study on edge extraction methods of the droplet image profile

Sijia Zhu; Han Yan; Wenqian Wu

doi:10.1117/12.750845

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15 November 2007 Study on edge extraction methods of the droplet image profile

Sijia Zhu, Han Yan, Wenqian Wu

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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678644 (2007) https://doi.org/10.1117/12.750845
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

It is a key technology to detect the edge of the droplet profile exactly for application in drop volume calculation, liquid target identification and liquid characteristics analysis. The droplet images in various stages during the drop growth are firstly acquired and stored real-timely through ICCD. After a series of preprocessing, including image cutting, noise filtering, image segmentation and filling, a proper edge detection method is chosen to extract the droplet image profile. The principle and algorithm of some classical and newly developed methods for edge detection are introduced and compared in detail, such as differential operator, Laplacian operator, improved Canny operator, wavelet transformation, mathematical morphology, fuzzy operator and fractal geometry. Wavelet transformation can be used effectively for extracting the droplet image profile, because of its advantages of multiple resolution, focus variation and edge enhancement. The image records of the droplet formation and the detected profile curves are presented.

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Sijia Zhu, Han Yan, and Wenqian Wu "Study on edge extraction methods of the droplet image profile", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678644 (15 November 2007); https://doi.org/10.1117/12.750845

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