C.J. Entuni* and T.M.A. Zulcaffle
Department of Electrical and Electronic Engineering, Universiti Malaysia Sarawak, Malaysia
Email: tiajaby@gmail.com
Received-07.07.2021, Revised-26.07.2021, Accepted-15.08.2021
Abstract: Most developing countries that rely on agricultural resources, such as India and Malaysia, still employ traditional techniques which are visual inspection to detect plant leaf diseases. Image processing is relatively new, cutting-edge technology in agriculture field to detect plant leaf diseases and the most important approach is through image segmentation. It works by segmenting meaningful information from diseased plant leaf image to be analysed and it is much simpler than traditional techniques. This article covers a survey on various image segmentation techniques such as K-Means, Otsu’s, Edge-based, Watershed and Region Growing. It also includes the discussion of advantages and disadvantages of each technique. Aside from that, the accuracy of segmentation achieved by each technique is also reviewed to describe their performance in detecting plant leaf diseases.
Keywords: Plant leaf diseases, Agricultural resources, Image processing, Image segmentation
REFERENCES
Adnan, N. and Nordin, S. M. (2021). How COVID 19 effect Malaysian paddy industry? Adoption of green fertilizer a potential resolution. In Environment, Development and Sustainability, 23(6).
Al-shakarji, N. M., Kassim, Y. M. and Palaniappan, K. (2017). Unsupervised learning method for plant and leaf segmentation. IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 31–34.
Chuanlei, Z., Shanwen, Z., Jucheng, Y., Yancui, S. and Jia, C. (2017). Apple leaf disease identification using genetic algorithm and correlation-based feature selection method. International Journal of Agriculture and Biology Engineering, 10(2), 74–83.
Fadzil, W. M., Rizam, S., Jailani, R. and Nooritawati, M. (2014). Orchid leaf disease detection using border segmentation techniques. IEEE Conference on Systems, Process and Control (ICSPC 2014), 2, 12–14.
Patel, A. and Joshi, M. B. (2017). A Survey on the Plant Leaf Disease Detection Techniques, International Journal of Agriculture and Biology Engineering, 10(2), 102-107.
Sankareswari, S. and Sivakamasundari, G. (2015). Diagnosis of grape leaf diseases using K-Means clustering and neural network. International Conference on Emerging Trends in Applications of Computing, 1–5.
Sibiya, M. and Sumbwanyambe, M. (2019). An algorithm for severity estimation of plant leaf diseases by the use of colour threshold image segmentation and Fuzzy Logic Inference: A proposed algorithm to update a “Leaf Doctor” application. AgriEngineering, 10(3), 205–219.