title: Comparison of autofocus methods for automated microscopy.
abstract: Traditional autofocus methods were designed for microscopes driven by single processor computers. As computers are developed that exploit massive parallelism when acquiring and analyzing images, parallel cellular logic techniques became available to focus automatically. This paper introduces the reader to both cellular logic techniques for autofocus and a new spectral moment autofocus measure. It then compares these methods with more traditional autofocus methods. It is shown that traditional methods based on measurements of image power-give the best results when tested on one set of real images and two sets of synthetic images. The next best methods are the cellular logic and spectral moment techniques, while the worst are those based on the image probability density function or histogram.
authors.affiliation: Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.
authors.forename: L
authors.initials: L
authors.lastname: Firestone
authors.forename: K
authors.initials: K
authors.lastname: Cook
authors.forename: K
authors.initials: K
authors.lastname: Culp
authors.forename: N
authors.initials: N
authors.lastname: Talsania
authors.forename: K
authors.initials: K
authors.lastname: Preston
mesh_terms: D001331:Automation / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D008128:Logic; D008853:Microscopy / Q000379:methods*; D013057:Spectrum Analysis / Q000379:methods