A coarse-to-fine auto-focusing algorithm for microscopic image

Yung Chun Liu, Fu Yu Hsu, Hsin Chen Chen, Yung Nien Sun, Yi Ying Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Auto-focusing is an important step in development a computer-aided evaluation system for diagnostic microscope. An auto-focusing algorithm can identify the best focus reliably and objectively, and prevents the tedious and time consuming steps of manual focusing. In this paper, a coarse-to-fine auto-focusing method is proposed based on a multi-resolution scheme which locates the focusing range by quadratic polynomial fitting in low resolution and achieves accurate focal point by using binary search in fine resolution. An algorithm was developed to identify the focal point under multiple image resolution with the Sum of Modified Laplacian (SML) as the focusing value. The main contribution of this system is to reduce the auto-focusing time. Comparing with the conventional binary search, the coarse-to-fine method only needs half of the time to accomplish auto-focusing. Using the proposed technique, the efficiency of auto-focusing system has been significantly improved.

Original languageEnglish
Title of host publicationProceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
Pages416-419
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, China
Duration: 2011 Jun 82011 Jun 10

Publication series

NameProceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

Other

Other2011 International Conference on System Science and Engineering, ICSSE 2011
Country/TerritoryChina
CityMacao
Period11-06-0811-06-10

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'A coarse-to-fine auto-focusing algorithm for microscopic image'. Together they form a unique fingerprint.

Cite this