Untitled Document
Not a member yet? Register for full benefits!

Username
Password
 Researchers develop optimal algorithm for determining focus error in eyes and cameras

This story is from the category Sensors
Printer Friendly Version
Email to a Friend (currently Down)

 

 

Date posted: 26/09/2011

University of Texas at Austin researchers have discovered how to extract and use information in an individual image to determine how far objects are from the focus distance, a feat only accomplished by human and animal visual systems until now.

Like a camera, the human eye has an auto-focusing system, but human auto-focusing rarely makes mistakes. And unlike a camera, humans do not require trial and error to focus an object.

Johannes Burge, a postdoctoral fellow in the College of Liberal Arts' Center for Perceptual Systems and co-author of the study, says it is significant that a statistical algorithm can now determine focus error, which indicates how much a lens needs to be refocused to make the image sharp, from a single image without trial and error.

"Our research on defocus estimation could deepen our understanding of human depth perception," Burge says. "Our results could also improve auto-focusing in digital cameras. We used basic optical modeling and well-understood statistics to show that there is information lurking in images that cameras have yet to tap."

The researchers' algorithm can be applied to any blurry image to determine focus error. An estimate of focus error also makes it possible to determine how far objects are from the focus distance.

See the full Story via external site: www.physorg.com



Most recent stories in this category (Sensors):

28/02/2017: DJI drones use plane avoidance tech

19/02/2017: Ford developing pothole alert system for drivers

08/02/2017: Pioneering chip extends sensors’ battery life

04/02/2017: Sensor Networks for Rangeland Animals

04/02/2017: Cardiff Uni bid to create osteoarthritis 'smart patch'

31/01/2017: Efficient time synchronization of sensor networks by means of time series analysis

12/01/2017: Uber to share data to help ease city congestion

23/12/2016: Electronic 'hairy skin' could give robots a more human sense of touch