Research Area:  Machine Learning

Abstract:

Plants can be seen everywhere in daily life and are closely connected with our lives. The recognition and classification of plants are of great significance to ecological and environmental protection. Traditional plant identification methods are complex, and experts cannot classify multiple plant species quickly. More and more researchers pay attention to image processing and pattern recognition and use them to identify and classify plant leaves quickly. Based on this, this paper summarizes and classifies the methods of plant leaf recognition in recent years. First, we analyze these studies and classify them using different features and classifiers, such as shape, texture, color features, support vector machines, K nearest neighbors, convolutional neural networks, and so on. Secondly, compare the recognition results of plant leaf recognition methods under different datasets. Finally, the recognition of plant leaves is summarized, and future research and development have prospected.

Keywords:  
Plant recognition
Feature extraction
Classification
convolutional neural networks
Machine Learning
Deep Learning

Author(s) Name:  Zhaobin Wang, Jing Cui & Ying Zhu

Publisher name:  Springer

DOI:  10.1007/s10462-022-10278-2

Volume Information:  

Paper Link:   https://link.springer.com/article/10.1007/s10462-022-10278-2