Abstract
Plant growth analysis is hard to do automatic. The burden of technique makes harder to process the algorithm. Thresholding and segmentation parts are huge part of the approaches. In this study 15 different thresholding algorithms were implemented and compared with images from field for plant growth analysis. To decrease execution time, the algorithm was implemented on GPU (Graphics Processing Unit) with CUDA (Compute Unified Device Architecture) language. Also, thresh-olding methods was applied on GPU. These are Huang's fuzzy, Intermodes, Isodata, Li's Minimum Cross Entropy, Kapur-Sahoo-Wong (Maximum Entropy), Mean, Minimum Error, Minimum, Moments, Otsu, Percentile, RenyiEntropy, Shanbhag, Triangle, and Yen thresholding algorithms. Each method investigated the thresholds on HSV histograms to find proper color values. After all process, threshold results for dynamic and constant values were listed and compared. Moreover, performance metrics were measured.
Original language | English |
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Title of host publication | 2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781479941575 |
DOIs | |
Publication status | Published - 25 Sept 2014 |
Event | 2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 - Beijing, China Duration: 11 Aug 2014 → 14 Aug 2014 |
Publication series
Name | 2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 |
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Conference
Conference | 2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 |
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Country/Territory | China |
City | Beijing |
Period | 11/08/14 → 14/08/14 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- CUDA
- Dynamic thresholding
- GPU programming
- Image processing
- Plant Growth Analysis