Plant identification method based on cloud model and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method

Abstract

The invention relates to a plant identification method based on a cloud model and a TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. The method comprises the following steps: constructing a plant shape feature specimen database; utilizing a trapezium-cloud model to compare the shape features of a plant to be identified with the plant shape feature specimen database to acquire a comparative membership between the plant to be identified and the shape feature specimen database, thus completing the primary identification of the plant to be identified; when a plurality of identification results exist, utilizing a normal cloud model to carry out accurate matching calculation on the retrieval results so as to acquire a comparative accurate membership between the plant to be identified and the shape feature specimen database; and comprehensively evaluating the membership by utilizing the TOPSIS method to identify the plant. The method can comprehensively evaluate the final identification result by adopting the TOPSIS method, and can completely, reasonably and accurately carry out advantage and disadvantage sequencing according to certain evaluation indexes, so that the evaluation process is clear, and the evaluation result is objective.

Description

technical field [0001] The invention belongs to the technical field of plant identification, and in particular relates to a plant identification method based on cloud model and TOPSIS method. Background technique [0002] Agricultural databases play an important role in the development and utilization of agricultural information resources. At present, agricultural organizations at home and abroad have built a large number of agricultural databases. Among them, the most famous agricultural database systems in the world include AGRIS, IFIS, AGRI-COLA, and CABI. Large agricultural databases, namely the Agricultural System Database (AGRIS) of the Food and Agriculture Organization of the United Nations, the International Food Information Database (IFIS), the USDA Agricultural Online Access Database (AGRI-COLA) and the International Center for Agricultural Biology database (CAB1). Representative plant databases in my country include: China National Agricultural Science Data Sharin...

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Problems solved by technology

[0005] However, the current technology still has the following problems: (1) The current image acquisition is basically through a scanner, the background is simple, image segmentation and description are relatively simple, and it is difficult to deal with complex backgrounds; (2) The image databases used by different researchers are different , it is difficult to compare the performance of the recognition effect, and it is difficult to use in practice; (3) the current image classification system can usually only deal with a few to a hundred kinds of plants, the scope is small, and it is difficult to achieve large-scale, multi-category plant identification

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