DocumentCode :
3573585
Title :
The uncut lawn cognition algorithm based on image analysis
Author :
Xi Lu ; Yu Liu ; Huijiang Du ; Shixin Xu
Author_Institution :
Dept. of Mech. Eng. & Autom., Zhejiang Sci-Tech Univ., Hangzhou, China
fYear :
2014
Firstpage :
5138
Lastpage :
5142
Abstract :
An algorithm was proposed for recognizing uncut lawn in order to improve the efficiency of robotic mowers. Image data were captured on uncut lawn. After operations on image data of edge detection, image binaryzation, and image erosion, freeman chain code was used for larger target contour extraction and contour filling, and then the filling area was thinned and the thinned skeleton was pruned. After these operations, the shape features like the length of grass and the ratio of grass length to width were used to recognize the uncut lawn. Collecting 50 images of the uncut lawn respectively on sunny days and overcast days. The experimental results show that this algorithm has good cognition properties, the cognition ratios of 50 images were 84% and 90%.
Keywords :
edge detection; feature extraction; image capture; image thinning; mobile robots; object recognition; robot vision; service robots; shape recognition; contour filling; edge detection; filling area thinning; freeman chain code; grass length; grass width; image analysis; image binarization; image data capture; image erosion; overcast days; robotic mowers; shape features; sunny days; target contour extraction; thinned skeleton pruning; uncut lawn cognition algorithm; uncut lawn recognition; Algorithm design and analysis; Automation; Cognition; Feature extraction; Filling; Image edge detection; Robots; robotic movers; shape features; target extraction; uncut lawn;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7053589
Filename :
7053589
Link To Document :
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