Title :
Recognizing and locating of objects using binocular vision system
Author :
Guo-Shing Huang ; Wen-Lang Zhang
Author_Institution :
Dept. of Electron. Eng., Nat. Chin-Yi Univ. of Technol., Taichung, Taiwan
fDate :
May 31 2013-June 2 2013
Abstract :
This paper examines how to recognize the dynamic object and find its position using a real-time binocular visual image system, which describes contours of the object using edge detection algorithm. The system finds the object of image with shape matched method, which procedures include color segmentation of input image, finding the candidate area of matching color histogram, binary image morphologic management, convex hull process, and finding the object and its contours. Image recognition technique is used to find the features of the object on the image plane. Intrinsic and extrmsic parameters of the features are captured using calibration board to form a fundamental matrix for analysis that increases the accuracy of corresponding points. Finally, it performs the three-dimensional reconstruction to combine and associate the feature messages with camera parameters. We can hence obtain three-dimensional coordinate information of the object with reference to the camera system. Experimental results demonstrated that the high achievable accuracy and stability of position coordinates reconstructed from the features and three dimensional coordinates of the object with the camera system´s real-time binocular visual subsystem that provides three-dimensional position coordinate for the robotic arms of an intelligent robot.
Keywords :
calibration; cameras; dexterous manipulators; edge detection; feature extraction; image colour analysis; image matching; image reconstruction; image segmentation; intelligent robots; object recognition; real-time systems; robot vision; shape recognition; binary image morphologic management; binocular vision system; calibration; camera parameters; camera system real-time binocular visual subsystem; color histogram matching; convex hull process; dynamic object recognition; edge detection algorithm; extrinsic parameters; feature messages; fundamental matrix; image recognition technique; input image color segmentation; intelligent robot; intrinsic parameters; object location; position coordinate stability; real-time binocular visual image system; robotic arms; shape matched method; three-dimensional position coordinate information; three-dimensional reconstruction; Accuracy; Cameras; Image color analysis; Robot kinematics; Robot vision systems; Visual systems; Binocular vision; camera calibration; coordination transform; edge detection algorithm; feature; intelligent robot;
Conference_Titel :
Advanced Robotics and Intelligent Systems (ARIS), 2013 International Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4799-0100-5
DOI :
10.1109/ARIS.2013.6573548