Research Article
Automatic Recognition of Tea Bud Image Based on Support Vector Machine
@INPROCEEDINGS{10.1007/978-3-030-67874-6_26, author={Wang Li and Rong Chen and Yuan-yuan Gao}, title={Automatic Recognition of Tea Bud Image Based on Support Vector Machine}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Support vector machine Image recognition Feature extraction}, doi={10.1007/978-3-030-67874-6_26} }- Wang Li
Rong Chen
Yuan-yuan Gao
Year: 2021
Automatic Recognition of Tea Bud Image Based on Support Vector Machine
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_26
Abstract
The existing recognition method of tea shoots is only to judge the single color or shape features, resulting in low recognition accuracy. Therefore, an automatic recognition method of tea shoots image based on support vector machine is designed. In this method, two kinds of image features, color and shape texture, are extracted from the tea bud image for discrimination. The RGB model is used to extract color features, and LBP/C operator is used to extract the shape and texture features of the bud. The extracted features are used as the feature vectors of the training samples, and support vector machine model training is carried out to obtain the support vector machine classifier, and the tea bud image is recognized. The experimental results show that the recognition rate, recall rate and comprehensive evaluation index of the method are higher than those of the traditional method, which proves that the method has high recognition accuracy and improves the recognition efficiency.
