Plant Leaf Disease Detection Using Image Processing: A Comprehensive Review




Plant Disease Detection, Image Processing, Feature Extraction, Segmentation, Classification


In this review paper, previous and current works for plant leaf disease detection have been studied. The traditional manual visual quality inspection cannot be defined systematically as this method is unpredictable and inconsistent. Moreover, it involves a remarkable amount of expertise in the field of plant disease diagnostics (phytopathology) in addition to the disproportionate processing times. Hence, image processing has been applied for the recognition of plant diseases. This paper has been divided into three main parts. In the first part, a comprehensive review based on algorithms is provided were the major algorithms and works conducted using image processing and artificial intelligence algorithms have been compared. The second part discusses the frameworks and compared the previous works. Then, a comprehensive discussion based on the accuracy of the results was provided. Based on the review conducted, a detailed explanation of the illnesses detection and classification performance is provided. Finally, the findings and challenges in plant leaf detection using image processing are summarized and discussed.


S. Bankar, A. Dube, P. Kadam, and D. Sunil, “Plant Disease Detection Techniques Using Canny Edge Detection & Color Histogram in Image Processing,” 2014. [Online]. Available:

S. H. Lee, C. S. Chan, S. J. Mayo, and P. Remagnino, “How deep learning extracts and learns leaf features for plant classification,” Pattern Recognit, vol. 71, pp. 1–13, Nov. 2017, doi: 10.1016/j.patcog.2017.05.015.

S. A. Tsaftaris, M. Minervini, and H. Scharr, “Machine Learning for Plant Phenotyping Needs Image Processing,” Trends Plant Sci, vol. 21, no. 12, pp. 989–991, Dec. 2016, doi: 10.1016/j.tplants.2016.10.002.

A. Fuentes, S. Yoon, and D. S. Park, “Deep Learning-Based Techniques for Plant Diseases Recognition in Real-Field Scenarios,” 2020, pp. 3–14. doi: 10.1007/978-3-030-40605-9_1.

J. Li, Y. Mi, G. Li, and Z. Ju, “CNN-Based Facial Expression Recognition from Annotated RGB-D Images for Human–Robot Interaction,” International Journal of Humanoid Robotics, vol. 16, no. 04, p. 1941002, Aug. 2019, doi: 10.1142/S0219843619410020.

P. Melnyk, Z. You, and K. Li, “A high-performance CNN method for offline handwritten Chinese character recognition and visualization,” Soft comput, vol. 24, no. 11, pp. 7977–7987, Jun. 2020, doi: 10.1007/s00500-019-04083-3.

D. Yang, S. Li, Z. Peng, P. Wang, J. Wang, And H. Yang, “MF-CNN: Traffic Flow Prediction Using Convolutional Neural Network and Multi-Features Fusion,” IEICE Trans Inf Syst, vol. E102.D, no. 8, pp. 1526–1536, Aug. 2019, doi: 10.1587/transinf.2018EDP7330.

S. K. Sundararajan, B. Sankaragomathi, and D. S. Priya, “Deep Belief CNN Feature Representation Based Content Based Image Retrieval for Medical Images,” J Med Syst, vol. 43, no. 6, p. 174, Jun. 2019, doi: 10.1007/s10916-019-1305-6.

K. Rajesh Babu, “Plant Disease Identification and Classification using Image Processing Depth Resolution in Non Stationary Thermal Wave Imaging Using Wavelet Transform View project,” 2019. [Online]. Available:

S. Raut, A. Fulsunge, and P. G. Student, “Plant Disease Detection inImage Processing Using MATLAB,” International Journal of Innovative Research in Science, Engineering and Technology (An ISO, vol. 3297, 2007, doi: 10.15680/IJIRSET.2017.0606034.

S. Arivazhagan, R. N. Shebiah, S. Ananthi, and S. V. Varthini, “Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features,” 2013. [Online]. Available:

M. Bhange and H. A. Hingoliwala, “Smart Farming: Pomegranate Disease Detection Using Image Processing,” in Procedia Computer Science, 2015, vol. 58, pp. 280–288. doi: 10.1016/j.procs.2015.08.022.

S. Pavithra, A. Priyadharshini, V. Praveena, and T. Monika, “Paddy Leaf Disease Detection Using Svm Classifier,” International Journal of communication and computer Technologies, vol. 3, no. 1, Jan. 2019, doi: 10.31838/ijccts/03.01.04.

Y. M. Oo and N. C. Htun, “Plant Leaf Disease Detection and Classification using Image Processing,” International Journal of Research and Engineering, vol. 5, no. 9, pp. 516–523, Nov. 2018, doi: 10.21276/ijre.2018.5.9.4.

U. Mokhtar, M. A. S. Ali, A. E. Hassenian, and H. Hefny, “Tomato leaves diseases detection approach based on Support Vector Machines,” in 2015 11th International Computer Engineering Conference (ICENCO), Dec. 2015, pp. 246–250. doi: 10.1109/ICENCO.2015.7416356.

K. R. Gavhale, U. Gawande, and K. O. Hajari, “Unhealthy region of citrus leaf detection using image processing techniques,” in International Conference for Convergence for Technology-2014, Apr. 2014, pp. 1–6. doi: 10.1109/I2CT.2014.7092035.

V. Pooja, R. Das, and V. Kanchana, “Identification of plant leaf diseases using image processing techniques,” in 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), Apr. 2017, pp. 130–133. doi: 10.1109/TIAR.2017.8273700.

G. Shrivastava and H. Patidar, “Rice Plant Disease Identification Decision Support Model Using Machine Learning,” ICTACT Journal on Soft Computing, p. 3, 2022, doi: 10.21917/ijsc.2022.0365.

A. Singh and H. Kaur, “Potato Plant Leaves Disease Detection and Classification using Machine Learning Methodologies,” IOP Conf Ser Mater Sci Eng, vol. 1022, no. 1, p. 012121, Jan. 2021, doi: 10.1088/1757-899X/1022/1/012121.

R. P. Narmadha and G. Arulvadivu, “Detection and measurement of paddy leaf disease symptoms using image processing,” in 2017 International Conference on Computer Communication and Informatics (ICCCI), Jan. 2017, pp. 1–4. doi: 10.1109/ICCCI.2017.8117730.

M. Ranjan, M. Rajiv Weginwar, N. Joshi, and A. Ingole, “Detection and Classification of Leaf Disease Using Artificial Neural Network,” 2015. [Online]. Available:

E. A. Abusham, “Image Processing Technique for the Detection of Alberseem Leaves Diseases Based on Soft Computing,” Artificial Intelligence & Robotics Development Journal, pp. 103–115, Jun. 2021, doi: 10.52098/airdj.202127.

A. Parikh, M. S. Raval, C. Parmar, and S. Chaudhary, “Disease detection and severity estimation in cotton plant from unconstrained images,” in Proceedings - 3rd IEEE International Conference on Data Science and Advanced Analytics, DSAA 2016, Dec. 2016, pp. 594–601. doi: 10.1109/DSAA.2016.81.

G. Ramkumar, R. Thandaiah Prabu, and A. Sabarivani, “An Effectual Plant Leaf Disease Detection using Deep Learning Network with IoT Strategies,” 2021. [Online]. Available:

M. A. Jasim and J. M. AL-Tuwaijari, “Plant Leaf Diseases Detection and Classification Using Image Processing and Deep Learning Techniques,” in 2020 International Conference on Computer Science and Software Engineering (CSASE), Apr. 2020, pp. 259–265. doi: 10.1109/CSASE48920.2020.9142097.

S. Sladojevic, M. Arsenovic, A. Anderla, D. Culibrk, and D. Stefanovic, “Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification,” Comput Intell Neurosci, vol. 2016, pp. 1–11, 2016, doi: 10.1155/2016/3289801.

P. Agarwal, “Plant Disease Detection and Classification Using Deep Neural Networks,” 2019. [Online]. Available:

M. Yogeshwari and G. Thailambal, “Automatic feature extraction and detection of plant leaf disease using GLCM features and convolutional neural networks,” Mater Today Proc, May 2021, doi: 10.1016/j.matpr.2021.03.700.

A. Devaraj, K. Rathan, S. Jaahnavi, and K. Indira, “Identification of Plant Disease using Image Processing Technique,” in 2019 International Conference on Communication and Signal Processing (ICCSP), Apr. 2019, pp. 0749–0753. doi: 10.1109/ICCSP.2019.8698056.

Md. A. Iqbal and K. H. Talukder, “Detection of Potato Disease Using Image Segmentation and Machine Learning,” in 2020 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), Aug. 2020, pp. 43–47. doi: 10.1109/WiSPNET48689.2020.9198563.

Mr. A. N. Patil and Miss. V. Pawar, “Detection and Classification of Plant Leaf Disease,” IARJSET, vol. 4, no. 4, pp. 72–75, Jan. 2017, doi: 10.17148/IARJSET/NCIARCSE.2017.20.

S. D.M., Akhilesh, S. A. Kumar, R. M.G., and P. C., “Image based Plant Disease Detection in Pomegranate Plant for Bacterial Blight,” in 2019 International Conference on Communication and Signal Processing (ICCSP), Apr. 2019, pp. 0645–0649. doi: 10.1109/ICCSP.2019.8698007.

S. B. Patil and S. K. Bodhe, “Leaf Disease Severity Measurement Using Image Processing,” 2011.

V. SBhong, “Study and Analysis of Cotton Leaf Disease Detection Using Image Processing,” Int J Adv Res Sci Eng Technol, vol. 3, no. 2, 2016, [Online]. Available:

IEEE Control Systems Society, IEEE Control Systems Society. Chapter Malaysia., and Institute of Electrical and Electronics Engineers, Orchid Leaf Disease Detection using Border Segmentation Techniques. 2014.

S. S. Sannakki, V. S. Rajpurohit, V. B. Nargund, and P. Kulkarni, “Diagnosis and classification of grape leaf diseases using neural networks” in 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), Jul. 2013, pp. 1–5. doi: 10.1109/ICCCNT.2013.6726616.

S. Chandramouleeswaran, M. Senthil Kumar, and A. Professor, “Plant Infection Detection Using Image Processing,” 2018. [Online]. Available:




How to Cite

M. N. Hasan, M. Mustavi, M. A. . Jubaer, M. T. Shahriar, and T. Ahmed, “Plant Leaf Disease Detection Using Image Processing: A Comprehensive Review”, Malaysian J. Sci. Adv. Tech., vol. 2, no. 4, pp. 174–182, Oct. 2022.