Name
Title | ||
|---|---|---|
A Predictive, Size-Invariant Convex Shape Detector For High-Speed And Accurate Image Processing |
Abstract | ||
|---|---|---|
In this paper a novel convex shape detector is presented suitable for high-speed image processing, regardless of the object's size. Its primary application is visual servoing in robotics, where an industrial robot is guided using visual information. In addition, it was found that this algorithm is also suitable for high-accurate applications, which was confirmed by experiment and comparison to existing algorithms. The focus of this paper is put on processing the image information rather than preparing the image using a number of morphological operators. The two main objectives are: achieving a high-accurate and high-speed convex shape detector. It is shown that both of these goals were achieved, by position accuracy within 1 pixel and a processing speed as low as 0.1ms. |
Year | Venue | Field |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO) | Computer vision,Image processing,Control engineering,Industrial robot,Pixel,Visual servoing,Operator (computer programming),Artificial intelligence,Invariant (mathematics),Detector,Robotics,Mathematics |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Kefer | 1 | 0 | 0.34 |
| Jihuan Tian | 2 | 0 | 0.34 |