Distance-dependent multimodal image registration for agriculture tasks

Ron Berenstein, Marko Hočevar, Tone Godeša, Yael Edan, Ohad Ben-Shahar

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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.

Original languageEnglish
Pages (from-to)20845-20862
Number of pages18
JournalSensors
Volume15
Issue number8
DOIs
StatePublished - 1 Aug 2015

Keywords

  • Artificial control points
  • Control points
  • Sensor fusion
  • Sensor registration

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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