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A Study on Classification for Leguminous Forage Based on Image Recognition Technology

Author: WangJingXuan
Tutor: FengQuan
School: Gansu Agricultural University
Course: Agricultural Mechanization Engineering
Keywords: Forage legumes Blades recognition Image processing PNN network BP network
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 102
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Abstract


Agriculture is the foundation of our national economy , and improve the efficiency of agricultural production and the degree of automation is the fundamental way to achieve the modernization of agricultural production . In recent years, legume forage acreage of alfalfa (Medicago sativa L.) , represented by expanding the alfalfa industry has been a great development , but a technical problem in insect pest control is also a legume forage cultivation management . The purpose of this study was to computer image recognition technology to build automatic detection and the visual type identification systems identify legume forage , and lay a foundation for the realization of spraying pesticide , grass pest so as to effectively prevent and control hazards . Typically, botany household labor method of plant classification , but the artificial classification of both time-consuming and inefficient . With the rapid development of computer technology , image processing and pattern recognition techniques in the field of information technology has been applied to plant classification . Relative to the 2 -dimensional structure of the three - dimensional structure of the plant flowers , plant leaves can easily be computerized . In this paper, computer image processing technology, based on the shape of the image characteristics of plant leaves legume forage for classification . By pretreatment of leaf images , extracting the contour of the blade . Extracted based on the shape feature of the blade : respectively, the longitudinal axis of the blade cross ratio , squareness , roundness , 8 geometric characteristics and seven images invariant moments . The PNN and BP neural network as a classifier to identify classification classification of forage legumes leaf images . Recognition results show that the average recognition rate of PNN network 85.1 % BP network average recognition rate of 82.4 % . Using a combination of the above methods , the development environment design to MATLAB7.0 is a summary of legume forage identification systems .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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