Crops Diagnosis Using Hurst Exponent Values in Fields Image Analysis
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FMPMSA2017_103Ekielski, Koronczok.pdf (649.3 KB)
Date
2017-11
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Dept. of Mach. Exploit. and Management of Prod. Processes, ULS in Lublin, Poland
Abstract
One of the branches of sustainable agriculture is the precision farming which assumes an individual approach to each plant. The main problem encountered by the precision agriculture is to quickly acquire and analyze good quality data assessing the condition of the crop. One of the fastest growing monitoring techniques is the analysis of images obtained from cameras placed on UAV. The studies used the chaos tools to determine Hurst exponent values received from images collected during UAV flights over the fields. The obtained results of image analysis indicated the presence of a strong dependency between the Hurst exponent values and state of crops. Images showed crops which are in good standing have been seen as strong organize objects represented by the mean Hurst exponent values from 0.8 to 0.87. Crops in which occurred the destruction of plants on the collected images were estimated by the Hurst exponent between 0.41 and 0.49 values, which indicates the presence of the characteristics of chaotic changes in the distribution of color attributes.
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Citation
Ekielski A., Koronczok J., Lorencki J., Czech T., Tulska E. 2017. Crops Diagnosis Using Hurst Exponent Values in Fields Image Analysis. [in:] Lorencowicz E. (ed.), Uziak J. (ed.), Huyghebaert B. (ed.). Farm Machinery and Processes Management in Sustainable Agriculture, 9th Int. Scient. Symp. ULS Lublin, p. 103-108