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Sensors 2017, 17(6), 1425; doi:10.3390/s17061425

Novel Descattering Approach for Stereo Vision in Dense Suspended Scatterer Environments

1
Department of Mechanical Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea;
2
Unmanned Safety Robot Research Center, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea;
*
Authors to whom correspondence should be addressed.
Received: 19 May 2017 / Revised: 13 June 2017 / Accepted: 14 June 2017 / Published: 17 June 2017
(This article belongs to the Section Physical Sensors)
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Abstract

In this paper, we propose a model-based scattering removal method for stereo vision for robot manipulation in indoor scattering media where the commonly used ranging sensors are unable to work. Stereo vision is an inherently ill-posed and challenging problem. It is even more difficult in the case of images of dense fog or dense steam scenes illuminated by active light sources. Images taken in such environments suffer attenuation of object radiance and scattering of the active light sources. To solve this problem, we first derive the imaging model for images taken in a dense scattering medium with a single active illumination close to the cameras. Based on this physical model, the non-uniform backscattering signal is efficiently removed. The descattered images are then utilized as the input images of stereo vision. The performance of the method is evaluated based on the quality of the depth map from stereo vision. We also demonstrate the effectiveness of the proposed method by carrying out the real robot manipulation task. View Full-Text
Keywords: low visibility; backscattering; descattering; defogging; stereo vision low visibility; backscattering; descattering; defogging; stereo vision
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Nguyen, C.D.T.; Park, J.; Cho, K.-Y.; Kim, K.-S.; Kim, S. Novel Descattering Approach for Stereo Vision in Dense Suspended Scatterer Environments. Sensors 2017, 17, 1425.

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