Finding colored objects under different illumination conditions in robotic applications

Dietmar Legenstein; Markus Vincze; Stefan Chroust

doi:10.1117/12.403783

11 October 2000 Finding colored objects under different illumination conditions in robotic applications

Dietmar Legenstein, Markus Vincze, Stefan Chroust

Proceedings Volume 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision; (2000) https://doi.org/10.1117/12.403783
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States

Abstract

Color information is very useful for object recognition, but the measured image color of objects depends on the scene illumination. Human vision exhibits color constancy for an object under a wide range of illumination conditions. A similar ability is required if computer vision systems are used to recognize objects in uncontrolled environments. Until now there is no satisfying approach for finding a colored object under different illuminations and using different cameras. To find the colored object, the following approach is proposed and has been verified with several demonstrations. The first step is to take a picture of the known object and a reference template of eighteen colored strips. Using the color values of the reference template the object color can be related to the reference colors. The key idea is that the robot can take the template with the 18 colored strips with it. In other rooms with other illumination conditions the robot can look at this reference template and calibrate its camera to different illumination conditions. The color calibration of the camera is achieved with a transformation matrix and the standard deviation of the color transformation is used to evaluate the quality of the transformation. Under the new illumination conditions, this transformation is used to search for the color of the object in a new room. The found object color is related to the reference values of the sample using the transformation into the new color space. The colored object itself is found using the multi-spectral classification via Gaussian distribution. First demonstrations indicate that this approach is very robust against different illumination conditions ranging form neon light to direct sun light and can be used rather simple by each robot.

Citation Download Citation

Dietmar Legenstein, Markus Vincze, and Stefan Chroust "Finding colored objects under different illumination conditions in robotic applications", Proc. SPIE 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, (11 October 2000); https://doi.org/10.1117/12.403783

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available