Application of image recognition technology in census of national traditional Chinese medicine resources
Received:November 03, 2017  
DOI:
KeyWord:national census of Chinese medicine resources  image recognition technology  application discussion
Author NameAffiliationE-mail
ZHANG Xiao-bo State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
GE Xiao-guang State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
JIN Yan State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
SHI Ting-ting State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
WANG Hui State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
LI Meng State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
JING Zhi-xian State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
GUO Lan-ping State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China  
HUANG Lu-qi State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing 100700, China huangluqi01@126.com 
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Abstract:
      With the development of computer and image processing technology, image recognition technology has been applied to the national medicine resources census work at all stages.Among them:①In the preparatory work, in order to establish a unified library of traditional Chinese medicine resources, using text recognition technology based on paper materials, be the assistant in the digitalization of various categories related to Chinese medicine resources; to determine the representative area and plots of the survey from each census team, based on the satellite remote sensing image and vegetation map and other basic data, using remote sensing image classification and other technical methods to assist in determining the key investigation area. ②In the process of field investigation, to obtain the planting area of Chinese herbal medicine was accurately, we use the decision tree model, spectral feature and object-oriented method were used to assist the regional identification and area estimation of Chinese medicinal materials.③In the process of finishing in the industry, in order to be able to relatively accurately determine the type of Chinese medicine resources in the region, based on the individual photos of the plant, the specimens and the name of the use of image recognition techniques, to assist the statistical summary of the types of traditional Chinese medicine resources. ④In the application of the results of transformation, based on the pharmaceutical resources and individual samples of medicinal herbs, the development of Chinese medicine resources to identify APP and authentic herbs 3D display system, assisted the identification of Chinese medicine resources and herbs identification characteristics. The introduction of image recognition technology in the census of Chinese medicine resources, assisting census personnel to carry out related work, not only can reduce the workload of the artificial, improve work efficiency, but also improve the census results of information technology and sharing application ability. With the deepening of the work of Chinese medicine resources census, image recognition technology in the relevant work will also play its unique role.
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