The aim of this thesis is to develop a stereo vision system to locate and
classify objects moving on a conveyor belt. The vision system determines the
locations of the objects with respect to a world coordinate system and class of the
objects. In order to estimate the locations of the objects, two cameras placed at
different locations are used. Image processing algorithms are employed to extract
some features of the objects. These features are fed to stereo matching and
classifier algorithms. The results of stereo matching algorithm are combined with
the calibration parameters of the cameras to determine the object locations.
Pattern classification techniques (Bayes and Nearest Neighbor classifiers) are
used to classify the objects. The linear velocity of the objects is determined by
using an encoder mounted to the shaft of the motor driving the conveyor belt. A
robot can plan a sequence of motion to pick the object from the conveyor belt by
using the output of the proposed system.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12605732/index.pdf |
| Date | 01 January 2005 |
| Creators | Bayraktar, Hakan |
| Contributors | Kaftanoglu, Bilgin |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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