Abstract
This paper presents a novel preprocessing method for detecting small objects of interest within a high-resolution image, applied to the problem of visually detecting possible aircraft collisions (Sense and Avoid) for UAV platforms. The method is based on superpixel image segmentation combined with subsequent statistical analysis and anomaly detection. The existence of a possible target within a superpixel is described in terms of how it affects the local superpixel statistics and this signature statistical profile is consequently used to identify regions of interest throughout the image. The approach eliminates upwards of 90% of the total image area, significantly reducing the workload of further processing stages.
Original language | English |
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Title of host publication | 2015 IEEE International Conference on Image Processing (ICIP 2015) |
Subtitle of host publication | Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 2229-2233 |
Number of pages | 5 |
ISBN (Electronic) | 9781479983391 |
ISBN (Print) | 9781479983407 |
DOIs | |
Publication status | Published - Jan 2016 |
Event | 2015 IEEE International Conference on Image Processing (ICIP) - Quebec City, ON, Canada Duration: 27 Sept 2015 → 30 Sept 2015 |
Conference
Conference | 2015 IEEE International Conference on Image Processing (ICIP) |
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Country/Territory | Canada |
City | Quebec City, ON |
Period | 27/09/15 → 30/09/15 |
Keywords
- Anomaly Detection
- Sense and Avoid
- Statistical Detector
- Superpixels
- Context
- Measurement
- Standards
- Aircraft
- Visualization
- Detectors
- Image segmentation