| Autor: |
Ogata, Taiki, Yukisawa, Taigo, Arai, Tamio, Ueyama, Tsuyoshi, Takada, Toshiyuki, Ota, Jun |
| Předmět: |
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| Zdroj: |
IEEJ Transactions on Electrical & Electronic Engineering; Dec2017 Supplement S2, Vol. 12, pS49-S55, 7p |
| Abstrakt: |
This study aims at automating the design of the image-recognition algorithm and the image-acquisition environment for an industrial picking system. Here for the image-recognition algorithm, a preprocessing image parameter and a discriminator using local features in images are targeted. For the image-acquisition environment, the camera distance from the target objects and the illumination strength of each RGB color are considered. The problem is formulated as an optimization problem, and a method is proposed to derive solutions using a two-phase random multistart local optimization for the image-acquisition environment and the image-recognition algorithm. In addition, experiment-based optimization is made to deal with the uncertainty of the capturing environment. Furthermore, positions and angles are considered in a robot coordinate system to simplify the image-acquisition process. The three evaluation experiments targeting objects with different surface characteristics are conducted. The results show that the proposed system successfully designed parameter sets for the image-acquisition environment and the image-recognition algorithm that suited the characteristics of the target objects. The object recognition rate, that is, F measure, is 1 for all objects in all the three experiments. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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