Robust mosaicking of maize fields from aerial imagery
Premise Aerial imagery from small unmanned aerial vehicle systems is a promising approach for high‐throughput phenotyping and precision agriculture. A key requirement for both applications is to create a field‐scale mosaic of the aerial imagery sequence so that the same features are in registration,...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-08-01
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| Series: | Applications in Plant Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/aps3.11387 |
| _version_ | 1819142929836408832 |
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| author | Rumana Aktar Dewi Endah Kharismawati Kannappan Palaniappan Hadi Aliakbarpour Filiz Bunyak Ann E. Stapleton Toni Kazic |
| author_facet | Rumana Aktar Dewi Endah Kharismawati Kannappan Palaniappan Hadi Aliakbarpour Filiz Bunyak Ann E. Stapleton Toni Kazic |
| author_sort | Rumana Aktar |
| collection | DOAJ |
| description | Premise Aerial imagery from small unmanned aerial vehicle systems is a promising approach for high‐throughput phenotyping and precision agriculture. A key requirement for both applications is to create a field‐scale mosaic of the aerial imagery sequence so that the same features are in registration, a very challenging problem for crop imagery. Methods We have developed an improved mosaicking pipeline, Video Mosaicking and summariZation (VMZ), which uses a novel two‐dimensional mosaicking algorithm that minimizes errors in estimating the transformations between successive frames during registration. The VMZ pipeline uses only the imagery, rather than relying on vehicle telemetry, ground control points, or global positioning system data, to estimate the frame‐to‐frame homographies. It exploits the spatiotemporal ordering of the image frames to reduce the computational complexity of finding corresponding features between frames using feature descriptors. We compared the performance of VMZ to a standard two‐dimensional mosaicking algorithm (AutoStitch) by mosaicking imagery of two maize (Zea mays) research nurseries freely flown with a variety of trajectories. Results The VMZ pipeline produces superior mosaics faster. Using the speeded up robust features (SURF) descriptor, VMZ produces the highest‐quality mosaics. Discussion Our results demonstrate the value of VMZ for the future automated extraction of plant phenotypes and dynamic scouting for crop management. |
| first_indexed | 2024-12-22T12:18:10Z |
| format | Article |
| id | doaj.art-5800faae9a544324ab71ea87cf3fd205 |
| institution | Directory Open Access Journal |
| issn | 2168-0450 |
| language | English |
| last_indexed | 2024-12-22T12:18:10Z |
| publishDate | 2020-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applications in Plant Sciences |
| spelling | doaj.art-5800faae9a544324ab71ea87cf3fd2052022-12-21T18:26:04ZengWileyApplications in Plant Sciences2168-04502020-08-0188n/an/a10.1002/aps3.11387Robust mosaicking of maize fields from aerial imageryRumana Aktar0Dewi Endah Kharismawati1Kannappan Palaniappan2Hadi Aliakbarpour3Filiz Bunyak4Ann E. Stapleton5Toni Kazic6Department of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USADepartment of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USADepartment of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USADepartment of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USADepartment of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USADepartment of Biology and Marine Biology University of North Carolina Wilmington North Carolina USADepartment of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USAPremise Aerial imagery from small unmanned aerial vehicle systems is a promising approach for high‐throughput phenotyping and precision agriculture. A key requirement for both applications is to create a field‐scale mosaic of the aerial imagery sequence so that the same features are in registration, a very challenging problem for crop imagery. Methods We have developed an improved mosaicking pipeline, Video Mosaicking and summariZation (VMZ), which uses a novel two‐dimensional mosaicking algorithm that minimizes errors in estimating the transformations between successive frames during registration. The VMZ pipeline uses only the imagery, rather than relying on vehicle telemetry, ground control points, or global positioning system data, to estimate the frame‐to‐frame homographies. It exploits the spatiotemporal ordering of the image frames to reduce the computational complexity of finding corresponding features between frames using feature descriptors. We compared the performance of VMZ to a standard two‐dimensional mosaicking algorithm (AutoStitch) by mosaicking imagery of two maize (Zea mays) research nurseries freely flown with a variety of trajectories. Results The VMZ pipeline produces superior mosaics faster. Using the speeded up robust features (SURF) descriptor, VMZ produces the highest‐quality mosaics. Discussion Our results demonstrate the value of VMZ for the future automated extraction of plant phenotypes and dynamic scouting for crop management.https://doi.org/10.1002/aps3.11387aerial imagerycrop field imagerymaizemosaickingsmall unmanned aerial system (sUAS)video summarization |
| spellingShingle | Rumana Aktar Dewi Endah Kharismawati Kannappan Palaniappan Hadi Aliakbarpour Filiz Bunyak Ann E. Stapleton Toni Kazic Robust mosaicking of maize fields from aerial imagery Applications in Plant Sciences aerial imagery crop field imagery maize mosaicking small unmanned aerial system (sUAS) video summarization |
| title | Robust mosaicking of maize fields from aerial imagery |
| title_full | Robust mosaicking of maize fields from aerial imagery |
| title_fullStr | Robust mosaicking of maize fields from aerial imagery |
| title_full_unstemmed | Robust mosaicking of maize fields from aerial imagery |
| title_short | Robust mosaicking of maize fields from aerial imagery |
| title_sort | robust mosaicking of maize fields from aerial imagery |
| topic | aerial imagery crop field imagery maize mosaicking small unmanned aerial system (sUAS) video summarization |
| url | https://doi.org/10.1002/aps3.11387 |
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