Difference between revisions of "Visual Systems for Robots"
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* ''try to eliminate holes in object by'' Process / Binary / Dilate ''and'' Process / Binary / Erode | * ''try to eliminate holes in object by'' Process / Binary / Dilate ''and'' Process / Binary / Erode | ||
* ''try'' Process / Binary / Skeletonize | * ''try'' Process / Binary / Skeletonize | ||
| + | |||
* ''restart'' ImageJ | * ''restart'' ImageJ | ||
* ''open'' pic1.jpg | * ''open'' pic1.jpg | ||
* ''start segmentation to 2 colors by'' Plugins / Segmentation / k-means clustering ''(select two colors)'' | * ''start segmentation to 2 colors by'' Plugins / Segmentation / k-means clustering ''(select two colors)'' | ||
| − | * ''return to the opened'' pic1.jpg ''and three times apply'' Process /Smooth | + | * ''return to the opened'' pic1.jpg ''and three times apply'' Process /Smooth ''then again perform the same segmentation'' |
| − | ''then again | ||
* ''compare the two segmented images and select better'' | * ''compare the two segmented images and select better'' | ||
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| − | start Octave or Matlab | + | * ''restart'' ImageJ |
| − | change directory to directory with this training by cd | + | * ''open'' pic2.jpg |
| − | launch tr2 | + | * ''apply'' Process / Filters / Gaussian Blur / 1.0 |
| + | * ''apply'' Process / Find edges | ||
| + | * ''apply'' Process / Binary / Make Binary | ||
| + | * ''apply thinning by'' Process / Binary / Skeletonize | ||
| + | |||
| + | |||
| + | * start Octave or Matlab | ||
| + | * change directory to directory with this training by <FONT Color="green"><TT>cd 'C:\Work\part2'</TT></FONT> | ||
| + | * launch <FONT Color="green"><TT>tr2</TT></FONT> | ||
Revision as of 06:10, 6 July 2010
by RNDr. Andrej Lúčny, PhD. (MicroStep-MIS, Ltd., Slovakia) presented at the Robotic Summer School 2010
- download accompanying workfiles Media:visual.zip
- unzip (to C:\Work recommended)
Part 1: Training on input image mainpulation
- start ImageJ
- open pic1.jpg
- Image / Color /
RGB SplitSplit Channels - apply Image / Lookup Tables / Red to pic1.jpg (red)
- apply Image / Lookup Tables / Green to pic1.jpg (green)
- apply Image / Lookup Tables / Blue to pic1.jpg (blue)
- close everything
- open pic1.jpg
- apply Image / Type / 8bit to get gray image
- apply Process / Binary / Make Binary to get binary image
- start Octave or Matlab
- change directory to directory with this training using the cd 'C:\Work\part1'
- launch tr1
Part 2: Training on 2D processing
- start ImageJ
- open pic1.jpg
- turn it grayscale: Image / Type / 8bit
- descrease noise by threshold: Image / Adjust / Threshold
- select Black & White from menu
- move with low and high end of range to emphasize the seen objects
- Apply and close the threshold window
- make the image binary: Process / Binary / Make binary
- if the picture contains now black object on white background, change it to white object on black background: Image / Lookup Tables / Invert LUT
- try to eliminate holes in object by Process / Binary / Dilate and Process / Binary / Erode
- try Process / Binary / Skeletonize
- restart ImageJ
- open pic1.jpg
- start segmentation to 2 colors by Plugins / Segmentation / k-means clustering (select two colors)
- return to the opened pic1.jpg and three times apply Process /Smooth then again perform the same segmentation
- compare the two segmented images and select better
- restart ImageJ
- open pic2.jpg
- apply Process / Filters / Gaussian Blur / 1.0
- apply Process / Find edges
- apply Process / Binary / Make Binary
- apply thinning by Process / Binary / Skeletonize
- start Octave or Matlab
- change directory to directory with this training by cd 'C:\Work\part2'
- launch tr2
