Visual Systems for Robots

by RNDr. Andrej Lúčny, PhD. (MicroStep-MIS, Ltd., Slovakia) presented at the Robotic Summer School 2010

• download accompanying workfiles Media:visual.zip

Part 1: Training on input image mainpulation

• start ImageJ
• open pic1.jpg
• Image / Color / RGB Split Split 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 and move with low and high end of range to emphasize the seen objects. Then 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 parform 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 launch tr2