A comprehensive survey on leaf disease identification & classification

被引:17
|
作者
Bhagat, Monu [1 ]
Kumar, Dilip [1 ]
机构
[1] NIT Jamshedpur, Dept Comp Sci & Engn, Jamshedpur, Jharkhand, India
关键词
Leaf disease; Artificial intelligence; Classification; Feature selection; Deep learning; ANN; SVM; CNN; RF; DL architecture; Visualization; PLANT-DISEASE; NEURAL-NETWORK; DEEP; SEGMENTATION; OPTIMIZATION; RECOGNITION; INDEXES; LEAVES; NITRATE; SYSTEM;
D O I
10.1007/s11042-022-12984-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents survey on various techniques used to classify plants and its disease. Classification is concerned with classifying each sample into different classes. Classification is a method of separating a healthy and diseased leaf on its morphological features such as texture, color, shape, pattern and so on. Due to resemblance in the visual properties among plants, sorting and classification are complicated to carry out especially in large area. There are various methods based on image processing techniques and computer vision. Choosing the suitable classification technique is quite difficult as the result varies on different input data. Classification of leaf diseases in plants has wide applications in different fields such as agriculture and biological research. This paper provides a general idea of few existing methods, its pros and cons, state of art of different techniques used by several authors in leaf disease identification and classification such as preprocessing techniques, feature extraction and selection techniques, datasets used, classifiers and performance metrics. Apart from these some challenges and research gaps are identified and their probable solutions are pointed out.
引用
收藏
页码:33897 / 33925
页数:29
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