machine vision software douglas destro oct. 20, 2014
TRANSCRIPT
Review
“It is the automatic extraction of information from digital images”
What is Machine Vision?
Parts of a Machine Vision System
LightingLens
SensorVision ProcessingCommunication
OverviewA bit of history and current state
Vision technology started in the 50’s, but the widespread use in industry arouse in the 80’s and 90’s
Early Automatix machine vision system (1983)
OverviewA bit of history and current state
Today, we can find different types of software that are very sophisticated, capable of complex analysis, and user-friendly.
OverviewWhere?
Virtually, every Machine Vision System uses software for image processing, analysis, and communication. It is a key component for its
efficiency and speed.
OverviewWhat? When?
There are four common uses of Machine Vision software
DecodingLocation
Counting Measurement
Overview Supporting Technology
• Hardware RequirementsMicrosoft Windows PC: Core2Duo, 1 USB or 1 NetworkWork memory: > 256 MBDisplay: VGA 64 K or True Color
• Software RequirementsWindows XP (32 bit): SP3, 1 GB RAMWindows 7 (32, 64 bit): SP1, 2 GB
Histogram analysis and equalization
How to automatically brighten dark pixel values and darken light ones?
Performing a histogram equalization is to find an intensity mapping function f(I) such that the resulting histogram is
flat.
This is done by first computing the cumulative distribution function, then applying f(I) = c(I)
Limitations
Lack of contrast (muddy looking)
Noise in dark regions can be amplified and become more visible
There are ways to mitigate these problems:
Using a linear blend between the cumulative distribution function and the identity transform
Standards
http://www.emva.org/cms/upload/Marketing_edocs_download/FSF_Vision_Standard
s_Brochure_A4_screen.pdf
Class Application
http://nifty.stanford.edu/2011/parlante-image-puzzle/
References
http://en.wikipedia.org/wiki/Machine_vision#Market
http://www.emva.org/cms/upload/Marketing_edocs_download/FSF_Vision_Standards_Brochure_A4_screen.pdf
https://www.youtube.com/watch?v=1IF3udt5ClI
http://nifty.stanford.edu/2011/parlante-image-puzzle/https://www.youtube.com/watch?v=1IF3udt5ClI