A new auto-focusing algorithm for optical microscope based automated system

被引：0

作者：

Song, Yu ^{[1
]}

Li, Mantian ^{[1
]}

Sun, Lining ^{[1
]}

机构：

[1] Harbin Inst Technol, Inst Robot, Harbin 150006, Hei Long Jiang, Peoples R China

来源：

2006 9TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION, VOLS 1- 5 | 2006年

关键词：

optical microscope; auto-focusing; SUSAN algorithm; similarity function;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Pixel-based auto-focusing is a long-standing topic in the literatures. It involves three main parameters: Region of Interest (ROI), image sharpness function and global maximum searching algorithm. As the mathematical description of image sharpness, sharpness function is the core issue for realizing robust auto-focusing. In this paper, the existing sharpness functions are summarized and grouped firstly, then a new space domain SUSAN (Smallest Univalue Segment Assimilating Nucleus) based sharpness function is proposed. The key problem in proposed algorithm is selecting a suitable similarity function to measure the similarities of the sampling pixel and its neighbors. In experiments, 8 similarity functions are analyzed and evaluated. Based on the evaluation results, a rough/fine two grades global maximum searching strategy is designed to realize fast and robust auto-focusing. At last, experiments verify the validity of the proposed auto-focusing algorithm.

引用

页码：1110 / +

页数：2

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