Microscope Vision Software
m (Added picture of command line interface.) |
m |
||
| Line 1: | Line 1: | ||
=MiCRoN Microscope Vision Software= | =MiCRoN Microscope Vision Software= | ||
| − | == | + | ==Implementation== |
| + | Computer vision for microscopes has to deal with the problem of limited depth of field. But instead of trying to overcome this, one can actually use the depth information concealed in this images to achieve real-time object recognition for microscopes. | ||
| + | |||
| + | Employing algorithms based on '''sobel edge detection''', '''geometric hashing''' and based on the '''bounded hough transform''', it was possible to recognise two micro-objects in around 300 milliseconds allowing '''4 degrees of freedom''' and then '''track them''' in consecutive frames '''with rates of up to 15 frames per second'''! | ||
| + | |||
| + | The software provides a '''framework''' to integrate and test different algorithms for recognition and tracking of multiple rigid objects. The parameters are stored in an XML file. The software offers a '''programmer's application interface''', which hides the inherent complexity (black-box principle), so that the '''vision-system''' can be integrated easily in a higher level system! | ||
| + | |||
| + | ==Results== | ||
| + | By using focus-stacks as models it was possible to provide '''real-time object recognition of multiple micro-objects''' in up to 4 degrees-of-freedom. The micro-objects are not required to stay at a fixed distance to the camera any more. Novel automated procedures in biology and micro-technology are thus conceivable. | ||
| + | |||
| + | '''Geometric hashing''' doesn't perform very well with increasing number of objects. Future work should also be about employing different types of features. Due to real-time constraints the choice is limited however. The tracking algorithm based on the '''bounded hough transform''' on the other hand performed very well. | ||
| + | |||
{|align=center | {|align=center | ||
|- | |- | ||
| Line 10: | Line 21: | ||
==Download== | ==Download== | ||
[[Image:MicronCommandLine.png|thumb|200px|right|Command line of the MiCRoN microscope vision software]] | [[Image:MicronCommandLine.png|thumb|200px|right|Command line of the MiCRoN microscope vision software]] | ||
| + | You can download the software (GPL license) and some test data to verify the results yourself! | ||
===micron-vision-1.9=== | ===micron-vision-1.9=== | ||
You first need to install [[Mimas#Mimas-1.4|version 1.4]] of the [[Mimas|Mimas Real-Time Computer Vision Library]] to be able to compile and run [http://vision.eng.shu.ac.uk/jan/micron-vision/micron-vision-1.9.tar.gz micron-vision-1.9] (514 kByte). | You first need to install [[Mimas#Mimas-1.4|version 1.4]] of the [[Mimas|Mimas Real-Time Computer Vision Library]] to be able to compile and run [http://vision.eng.shu.ac.uk/jan/micron-vision/micron-vision-1.9.tar.gz micron-vision-1.9] (514 kByte). | ||
Revision as of 15:10, 8 April 2006
Contents |
MiCRoN Microscope Vision Software
Implementation
Computer vision for microscopes has to deal with the problem of limited depth of field. But instead of trying to overcome this, one can actually use the depth information concealed in this images to achieve real-time object recognition for microscopes.
Employing algorithms based on sobel edge detection, geometric hashing and based on the bounded hough transform, it was possible to recognise two micro-objects in around 300 milliseconds allowing 4 degrees of freedom and then track them in consecutive frames with rates of up to 15 frames per second!
The software provides a framework to integrate and test different algorithms for recognition and tracking of multiple rigid objects. The parameters are stored in an XML file. The software offers a programmer's application interface, which hides the inherent complexity (black-box principle), so that the vision-system can be integrated easily in a higher level system!
Results
By using focus-stacks as models it was possible to provide real-time object recognition of multiple micro-objects in up to 4 degrees-of-freedom. The micro-objects are not required to stay at a fixed distance to the camera any more. Novel automated procedures in biology and micro-technology are thus conceivable.
Geometric hashing doesn't perform very well with increasing number of objects. Future work should also be about employing different types of features. Due to real-time constraints the choice is limited however. The tracking algorithm based on the bounded hough transform on the other hand performed very well.
 |
 |
 |
 |
 |
 |
Download
You can download the software (GPL license) and some test data to verify the results yourself!
micron-vision-1.9
You first need to install version 1.4 of the Mimas Real-Time Computer Vision Library to be able to compile and run micron-vision-1.9 (514 kByte).
The online documentation is here and you may also want to download some test data
- Data for test test (1.67 MByte)
- Data for test test2 (1.08 MByte)
- Data for test povray (5.08 MByte)
- Data for test sphere (8.65 MByte)
See Also
External Links
- Online documentation of MiCRoN Microscope Vision Software
