AI Article Synopsis
- Image registration aligns multiple images of the same scene captured at different times, perspectives, or with different sensors, focusing on agricultural systems that use visual and thermal sensors.
- The research develops a method using a distance-dependent transformation matrix (DDTM), created through pre-calibration and compactly represented via regression functions.
- A unique experimental setup with Artificial Control Points (ACPs) and detection algorithms for both sensors demonstrates the effectiveness of this method through various experiments.
Article 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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570450 | PMC |
| http://dx.doi.org/10.3390/s150820845 | DOI Listing |
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