DocumentCode :
3415815
Title :
Depth estimation from monocular vision using image edge complexity
Author :
Haris, Sallehuddin Mohamed ; Zakaria, M.K. ; Nuawi, Mohd Zaki
Author_Institution :
Dept. of Mech. & Mater. Eng., Univ. Kebangsaan Malaysia, Bangi, Malaysia
fYear :
2011
fDate :
3-7 July 2011
Firstpage :
868
Lastpage :
873
Abstract :
Autonomous robotic arm motion requires the use of a control system in order to prevent collisions with the targeted object. Generally, in translational motion, as the camera approaches an object, the degree of complexity of the edges of the object image will change. This principle can be used to estimate the distance to a targeted object. This work introduces a novel statistical method, named Moment of Zoomed-Algorithm Kurtosis (MoZAK), which is based on the I-kaz method, as an indicator for motion system control. The MoZAK parameter, ℒc which represents the degree of complexity of image edges, is used to indicate if further actuation of the motor, or otherwise, is required. The method is compared to conventional statistical methods (standard deviation and kurtosis). Results indicate that the MoZAK method presents a viable distance estimator compared to conventional statistical methods.
Keywords :
manipulators; motion control; robot vision; statistical analysis; MoZAK method; Moment of Zoomed-Algorithm Kurtosis method; depth estimation; distance estimation; image edge complexity; monocular vision; motion system control; robotic arm motion; statistical method; translational motion; Cameras; Complexity theory; Estimation; Image edge detection; Robot vision systems; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2011 IEEE/ASME International Conference on
Conference_Location :
Budapest
ISSN :
2159-6247
Print_ISBN :
978-1-4577-0838-1
Type :
conf
DOI :
10.1109/AIM.2011.6027091
Filename :
6027091
Link To Document :
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