Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation
This paper addresses two tasks: (i) fixed-size objects such as hay bales are to be identified in an aerial image for a given reference image of the object, and (ii) variable-size patches such as areas on fields requiring spot spraying or other handling are to be identified in an image for a given sm...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S277237552400340X |
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| author | Mogens Plessen |
| author_facet | Mogens Plessen |
| author_sort | Mogens Plessen |
| collection | DOAJ |
| description | This paper addresses two tasks: (i) fixed-size objects such as hay bales are to be identified in an aerial image for a given reference image of the object, and (ii) variable-size patches such as areas on fields requiring spot spraying or other handling are to be identified in an image for a given small-scale reference image. Both tasks are related. The second differs in that identified sub-images similar to the reference image are further clustered before patches contours are determined by solving a traveling salesman problem. Both tasks are complex in that the exact number of similar sub-images is not known a priori. The main discussion of this paper is presentation of an acceleration mechanism for sub-image search that is based on a transformation of an image to multivariate time series along the RGB-channels and subsequent segmentation to reduce the 2D search space in the image. Two variations of the acceleration mechanism are compared to exhaustive search on diverse synthetic and real-world images. Quantitatively, proposed method results in solve time reductions of up to 2 orders of magnitude, while qualitatively delivering comparative results, thereby highlighting the effect of the acceleration mechanism. Proposed method is neural network-free and does not use any image pre-processing. |
| format | Article |
| id | doaj-art-803cc45aa1c24ff7899fbd69ba7462f9 |
| institution | DOAJ |
| issn | 2772-3755 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-803cc45aa1c24ff7899fbd69ba7462f92025-08-20T02:52:20ZengElsevierSmart Agricultural Technology2772-37552025-03-011010073610.1016/j.atech.2024.100736Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentationMogens Plessen0Findklein GmbH, SwitzerlandThis paper addresses two tasks: (i) fixed-size objects such as hay bales are to be identified in an aerial image for a given reference image of the object, and (ii) variable-size patches such as areas on fields requiring spot spraying or other handling are to be identified in an image for a given small-scale reference image. Both tasks are related. The second differs in that identified sub-images similar to the reference image are further clustered before patches contours are determined by solving a traveling salesman problem. Both tasks are complex in that the exact number of similar sub-images is not known a priori. The main discussion of this paper is presentation of an acceleration mechanism for sub-image search that is based on a transformation of an image to multivariate time series along the RGB-channels and subsequent segmentation to reduce the 2D search space in the image. Two variations of the acceleration mechanism are compared to exhaustive search on diverse synthetic and real-world images. Quantitatively, proposed method results in solve time reductions of up to 2 orders of magnitude, while qualitatively delivering comparative results, thereby highlighting the effect of the acceleration mechanism. Proposed method is neural network-free and does not use any image pre-processing.http://www.sciencedirect.com/science/article/pii/S277237552400340XSub-image searchAerial imagesTime seriesVariable-size patchesSpot spraying |
| spellingShingle | Mogens Plessen Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation Smart Agricultural Technology Sub-image search Aerial images Time series Variable-size patches Spot spraying |
| title | Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation |
| title_full | Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation |
| title_fullStr | Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation |
| title_full_unstemmed | Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation |
| title_short | Accelerated sub-image search for variable-size patches identification based on virtual time series transformation and segmentation |
| title_sort | accelerated sub image search for variable size patches identification based on virtual time series transformation and segmentation |
| topic | Sub-image search Aerial images Time series Variable-size patches Spot spraying |
| url | http://www.sciencedirect.com/science/article/pii/S277237552400340X |
| work_keys_str_mv | AT mogensplessen acceleratedsubimagesearchforvariablesizepatchesidentificationbasedonvirtualtimeseriestransformationandsegmentation |