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Research of autofocus technology for human fecal microscopic image
Author(s): Xiangzhou Wang; Lin Liu; Ruqian Hao; Xiaohui Du; Jing Zhang; Juanxiu Liu; Guangming Ni; Yong Liu
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Paper Abstract

Fecal microscopic examination is a routine examination item to determine whether the digestive system is normal by analyzing formed elements. Traditional method is that doctor uses microscope eyepiece to observe sample smears. The efficiency is low, and examination results depend on doctor's experience level. Therefore, intelligent identification of formed elements is the main development direction of current fully automated fecal instruments. Unlike blood or urine samples, human fecal samples contain a lot of impurities, and sample stratification phenomenon is serious. So image quality assessment methods are difficult to find the sharpest image, affecting effectiveness of intelligent identification algorithm. In this paper, the microscopic image autofocus technology for human fecal samples is studied and divided into two parts: location and photographing. In location process, we use SMD algorithm to determine sample photographing interval. In photographing process, microscope platform zigzagged move in the interval to obtain each view's successively image sequences of different focal lengths. In order to accurately find the sharpest image in image sequence, we compared the difference between human eyes with 31 types of no-reference image quality assessment methods based on entropy, gradient, color, edge, contrast, similarity, and transform domain. Finally an improved Local TV algorithm was chose. Experimental results show that the improved Local TV algorithm is insensitive to changes in sample concentration with good robustness, and the accuracy rate can reach 94.26%. Our experimental results have some reference value for other focusing problems of complex microscopic images.

Paper Details

Date Published: 30 January 2019
PDF: 10 pages
Proc. SPIE 10841, 9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Meta-Surface-Wave and Planar Optics, 108410P (30 January 2019); doi: 10.1117/12.2506732
Show Author Affiliations
Xiangzhou Wang, Univ. of Electronic Science and Technology of China (China)
Lin Liu, Univ. of Electronic Science and Technology of China (China)
Ruqian Hao, Univ. of Electronic Science and Technology of China (China)
Xiaohui Du, Univ. of Electronic Science and Technology of China (China)
Jing Zhang, Univ. of Electronic Science and Technology of China (China)
Juanxiu Liu, Univ. of Electronic Science and Technology of China (China)
Guangming Ni, Univ. of Electronic Science and Technology of China (China)
Yong Liu, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 10841:
9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Meta-Surface-Wave and Planar Optics
Mingbo Pu; Xiaoliang Ma; Xiong Li; Minghui Hong; Changtao Wang; Xiangang Luo, Editor(s)

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