| In the precision agriculture,the technology is proposed for field crop growth information collection and analysis that adopts high-efficiency image acquisition technology and high-throughput computer digital image automatic processing technology,which is of great significance for guiding regional agricultural management and crop highyield cultivation.This technology not only saves a lot of manpower and financial resources,increases work efficiency,but also greatly improves the accuracy of data collection,and has broad application prospects.The segmentation of crop organs in images is a key step in the automatic processing of computer digital images,which directly determines the accuracy of information extraction.It is a major difficulty in the field of image processing.The rape is an important economic crop.Its flowering period is closely related to adaptability,yield and disease resistance,which directly affects the development planning of rapeseed industry.In order to establish an efficient collection platform for rapeseed flower information based on image acquisition and computer digital image automatic processing technology,this paper mainly carries out the following research work:(1)The effect of farm rape images segmented by the algorithm of color segmentation is researched.In this paper,the color characteristics of green crops are used to extract a RGB image,and then the image is performed according to the principle of green crop super green,and then mapped to three-dimensional space.This method can not only achieve the goal of the separation of soil and crops,but also extract the plants as well as rape flowers,and the segmentation of image is effectively and rapidly.(2)The template matching algorithm and the K-means clustering algorithm are used to extract rape flower effectively.Before the clustering algorithm,the template matching algorithm is used and is combined with the K-means clustering algorithm.The template matching algorithm can effectively locate and extract the rapeseed part of the image,which is the same as the template library,and the K-means clustering algorithm could achieve the pixels classification.To achieve the accurately segmentation of the rape flowers,firstly,a template library is created and the target area of the test image is located by the template matching algorithm.Then,the processed image will be converted to LAB color space,and classified by K-means clustering algorithm accurately again.Finally,the extracted rapeseed area will be processed by morphology operation.The experimental results indicate that this method can achieve to the goal of extracting the rape flowers completely,and it can effectively remove the negative impacts of the light.(3)An efficient information collection platform for rapeseed flower based on image acquisition and computer digital image automatic processing technology is established.Taking 40 rapeseed varieties as samples,the flowering stage information of rape collected by the above two image processing techniques is fitted with the real data of artificial investigation.The optimal rape flowering image segmentation technology is selected,and then a mathematical model for building an automatic collection platform for rapeseed flowering information is constructed. |
