@Article{jihpp.2020.010114,
AUTHOR = {Xuefei Du, Xuyu Xiang},
TITLE = {Research on Prevention of Citrus Anthracnose Based on Image Retrieval Technology},
JOURNAL = {Journal of Information Hiding and Privacy Protection},
VOLUME = {2},
YEAR = {2020},
NUMBER = {1},
PAGES = {11--19},
URL = {http://www.techscience.com/jihpp/v2n1/40332},
ISSN = {2637-4226},
ABSTRACT = {Citrus anthracnose is a common fungal disease in citrus-growing areas 
in China, which causes very serious damage. At present, the manual management 
method is time-consuming and labor-consuming, which reduces the control 
effect of citrus anthracnose. Therefore, by designing and running the image 
retrieval system of citrus anthracnose, the automatic recognition and analysis of
citrus anthracnose control were realized, and the control effect of citrus 
anthracnose was improved. In this paper, based on the self-collected and collated 
citrus anthracnose image database, we use three image features to realize an 
image retrieval system based on citrus anthracnose through SMV, AP clustering 
optimization. The results show that: 1) In the accuracy of image feature retrieval, 
Gist feature extraction > cumulative color histogram > Gabor texture feature; 2)
In the maximum divergence diversity retrieval, semi-supervised AP clustering 
retrieval > AP clustering retrieval > SVM relevance feedback results > initial 
retrieval. 3) Practice shows that this technology can reduce the workload of 
monitoring and management in the control process of citrus planting area, and 
promote the intelligent and efficient control of citrus anthracnose, which has high 
practical application value.},
DOI = {10.32604/jihpp.2020.010114}
}