Abstract
Classification and identification of plants are helpful for people to effectively understand and protect plants. The leaves of plants are the most important recognition organs. With the development of artificial intelligence and machine vision technology, plant leaf recognition technology based on image analysis is used to improve the knowledge of plant classification and protection. Deep learning is the abbreviation of deep neural network learning method and belongs to neural network structure. It can automatically learn features from big data and use artificial neural network based on back propagation algorithm to train and classify plant leaf samples. The main content of this paper is to extract plant leaf features and identify plant species based on image analysis. Firstly, plant leaf images are segmented by various methods, and then feature extraction algorithm is used to extract leaf shape and texture features from leaf sample images. Then the comprehensive characteristic information of plant leaves is formed according to the comprehensive characteristic information. In this paper, 50 plant leaf databases are tested and compared with KNN-based neighborhood classification, Kohonen network based on self-organizing feature mapping algorithm and SVM-based support vector machine. At the same time, the leaves of 7 different plants were compared and it was found that ginkgo leaves were easier to identify. For leaf images under complex background, good recognition effect has been achieved. Image samples of the test set are input into the learning model to obtain reconstruction errors. The class label of the test set can be obtained by reconstructing the deep learning model with the smallest error set. The results show that this method has the shortest recognition time and the highest correct recognition rate.
Highlights
There are abundant ecological resources on the earth, and plants are the most important part of ecological resources
RECOGNITION RATIO OF DIFFERENT FEATURES Using the same batch of blade samples, the artificial neural network based on backpropagation algorithm (BP algorithm), neighborhood classification based on K-Nearest Neighbor (KNN) algorithm, Kohonen network based on self-organizing feature mapping algorithm and support vector machine based on Support Vector Machine (SVM) algorithm are tested respectively
In this paper, the methods of plant leaf recognition based on digital image analysis are studied, and the current methods of plant leaf recognition are classified
Summary
There are abundant ecological resources on the earth, and plants are the most important part of ecological resources. Plants are known as green plants, including seed plants (angiosperms, gymnosperms), mossy plants and skillful vines, including flowering plants, mossy, vines, grass and so on. Plants are important to humans: photosynthetic synthetic starch provides food for humans; absorbs carbon dioxide to synthesize oxygen; regulates environmental temperature and humidity; absorbs toxic gases to purify the air. It is estimated that there are about hundreds of thousands of existing plants. The associate editor coordinating the review of this manuscript and approving it for publication was Chun-Wei Tsai. They have different shapes, structures and lifestyles. In order to understand and make better use of plants, plants must be classified
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