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Sensors (Basel). 2015 Aug 21;15(8):20845-62. doi: 10.3390/s150820845.

Distance-Dependent Multimodal Image Registration for Agriculture Tasks.

Author information

1
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel. berensti@bgu.ac.il.
2
Faculty of Mechanical Engineering, University of Ljubljana, Aškerčeva 6, Ljubljana 1000, Slovenia. marko.hocevar@fs.uni-lj.si.
3
Faculty of Mechanical Engineering, University of Ljubljana, Aškerčeva 6, Ljubljana 1000, Slovenia. tone.godesa@kis.si.
4
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel. yael@bgu.ac.il.
5
Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel. ben-shahar@cs.bgu.ac.il.

Abstract

Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use multimodal sensory systems and operate in natural environments. While not limited to any particular modalities; here we focus on systems with visual and thermal sensory inputs. Our approach is based on pre-calibrating a distance-dependent transformation matrix (DDTM) between the sensors; and representing it in a compact way by regressing the distance-dependent coefficients as distance-dependent functions. The DDTM is measured by calculating a projective transformation matrix for varying distances between the sensors and possible targets. To do so we designed a unique experimental setup including unique Artificial Control Points (ACPs) and their detection algorithms for the two sensors. We demonstrate the utility of our approach using different experiments and evaluation criteria.

KEYWORDS:

artificial control points; control points; sensor fusion; sensor registration

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