Abstract : According to the problem of the low matching accuracy rate and the low
speed in the matching technology for image search, we choose the image
of the strawberry diseases as the object of the research, to extract the
feature of strawberry diseases image and then do cluster analysis using
SPSS, and choose the feature combination according to the clustering
effect. Do search matching experiments on the feature combination by
KD-Tree matching algorithm respectively, and determine the
characteristics combination which search matching accuracy is higher by
comparing the results. This feature combination of strawberry powdery
mildew matching accuracy reached 83.3%, the deformity of strawberry
matching accuracy reached 60.0%, the aim is to provide the research
basis for rapid disease diagnosis on strawberry.
Daoliang Li; Yingyi Chen. 7th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2013, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-419 (Part I), pp.32-40, 2014, Computer and Computing Technologies in Agriculture VII. 〈10.1007/978-3-642-54344-9_5〉
https://hal.inria.fr/hal-01220666
Contributeur : Hal Ifip
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Soumis le : lundi 26 octobre 2015 - 16:56:25
Dernière modification le : mercredi 17 janvier 2018 - 10:44:15
Document(s) archivé(s) le : mercredi 27 janvier 2016 - 16:33:09
Chen Jianshu, Wang Jianlun, Wang Shuting, Liu Hao. The Matching Research of Strawberry Diseases Image Features Based on KD-Tree Search Method. Daoliang Li; Yingyi Chen. 7th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2013, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-419 (Part I), pp.32-40, 2014, Computer and Computing Technologies in Agriculture VII. 〈10.1007/978-3-642-54344-9_5〉. 〈hal-01220666〉
