Auto Focusing Algorithm Based on Largest Gray Gradient Summation

Laixian, 张来线 Zhang; Huayan, 孙华燕 Sun; Huichao, 郭惠超 Guo; Youchen, 范有臣 Fan

doi:10.3788/gzxb20134205.0605

Cited by 6 publications

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“…The image acquisition of liquid-based exfoliated cell slides requires automatic focusing, which is the key technology for high-quality image acquisition in the morphology inspection system [1]. The focusing effect is easy to be interfered by lens impurities and slide impurities [2]. The existence of slide impurities makes the focusing evaluation curve appear multi-extremum phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Automatic focusing technology of liquid-based exfoliated cell microscopic vision system

Wen¹,

Yang²,

Xiao³

2023

International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023)

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There are many impurities in the liquid-based exfoliated cell medical pathology slide and the phenomenon of multiple peaks in the evaluation of the front and back images, which may lead to the failure of focus in the automatic scanning and photographing of the system, and the low efficiency of the whole slide scanning. Based on the self-developed digital cell morphology inspection system, a comprehensive evaluation method for the sharpness of fusion image content preprocessing evaluation was proposed, which solved the problem of multi-peak discrimination in image sequence evaluation, and improved the image quality and efficiency of single-point focusing; During the whole scanning, the single-field focusing method of slide based on the traditional mountain-climbing method and the full-field efficient automatic scanning strategy based on multi-point and fixed-plane were designed to greatly improve the scanning speed. The experimental results show that the fusion image content pre-processing comprehensive evaluation method combined with the motion acquisition synchronous background operation strategy has a focus success rate of 98.68%, a single point focus time of 936 ms, and a full slide scan time of 142 s for the 200 field of view, which meets the requirements of clinical liquid-based cell morphology and pathology.

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Section: Introductionmentioning

confidence: 99%