A comparative analysis of vine leaves area measurement algorithms
Keywords:
leaf area; measurement algorithm; measurement errorAbstract
More and more frequently in contemporary scientific literature information can be found on the use of mobile devices such as video cameras and smartphones by which an area of different objects, for example – vine leaves, can be measured. Software, methods and algorithms for measuring area of leaves are described in general without methodological details. The necessary accuracy of the measurement is not commented too. In this paper a comparative analysis is made for four algorithms which are intended for measuring area of vine leaves in terms of measurement accuracy and performance of the computer system. In this study it is found that in the algorithm with nested loops the number of operations is increased but this is not influence on the precision of the measurement but the threshold level of binarization is affected on the precision of the measurement. This is proven by analyzing the execution time and operations number of various algorithms.
References
Chaudhary, P., Godara, S., Cheeran, A. N., & Chaud hari, A. K. (2012). Fast and accurate method for leaf area measurement. International Journal of Computer Applications, 49(9), 22-25.
Finley, D. (2006). Area of a polygon. Available at: http:// www.mathopenref.com [Accessed 12 December 2016]
Mladenov, M. I., Penchev, S. M., Dejanov, M. P., & Mustafa, M. S. (2011). Quality assessment of corn grain sample using color image analysis. Sensing and Instru mentation for Food Quality and Safety, 5(3-4), 111-127.
Orlando, F., Movedi, E., Coduto, D., Parisi, S., Branca doro, L., Pagani, V., Guarneri, T. & Confalonieri, R. (2016). Estimating Leaf Area Index (LAI) in Vineyards Using the PocketLAI Smart-App. Sensors, 16(12), 2004.
Sannakki, S., Rajpurohit, V., Nargund, V. & Kulkarni, P. (2013). Diagnosis and classification of grape leaf diseases using neural networks. In: Proceedings of 4th International Conference on Computing, Communica tions and Networking Technologies, July 4-6, 2013, Tiruchengode, India (pp. 1-5). IEEE.
Zlatev, Z., Ribarski, S. & Mladenov, M. (2014). Au tomatic measurement of Loin eye area with computer vision system. Agricultural Science and Technology, 6 (2), 224-227.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2017 Bulgarian Journal of Crop Science
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
