Automatic detection method and system for cotton five-euphylla period

Abstract

The invention discloses an automatic detection method for a cotton five-euphylla period. The automatic detection method comprises the following steps: (1) collecting a single-row plant image of a cotton field after final singling and splitting the image into subimages of a cotton single plant; carrying out color division and crop image division to obtain cotton plant subimages after final singling; (2) detecting edges and a skeleton of the plant according all the cotton plant subimages to obtain plant main stems; (3) detecting plant primary side stems on the two sides of the positions of the main stems, taking the primary side stems which form an acute angle on the upper sides of the main stems in the images of the two sides as side stems; and (4) by taking the crossed points of the side stems and the main stems as nodes, determining that a cotton field enters the five-euphylla period when detecting that the quantity of the subimages of two or more than two nodes accounts for more than 50% of the quantity of the cotton plant subimages after final singling. The invention further provides a system for realizing the method. The automatic detection method has an accurate detection result and strong instantaneity; and the automatic observation is realized and the manpower is saved.

Description

technical field [0001] The invention belongs to the intersection field of digital image processing and agricultural meteorological observation, and more specifically relates to a method and system for automatic detection of the five true leaf stages of cotton. Background technique [0002] Cotton is one of the main economic crops in China, and China's cotton output is also in the leading position in the world. The five true leaf stage of cotton is an important part of cotton growth and an important content of agricultural meteorological observation. [0003] For a long time, the relevant information of the cotton development period has been recorded mainly by manual observation and recording. The observation results will be affected by the subjective factors of the observers, resulting in relatively large errors; at the same time, due to the long growth cycle of cotton, cotton planting The range is relatively wide, and the method of only using manual observation is time-con...

AI Technical Summary

Problems solved by technology

[0004] In view of the above defects or improvement needs of the prior art, the present invention provides a method and system for automatic detection of the five true leaf stages of cotton, the purpose of which is to analyze the photos of cotton fields by image processing methods, thereby judging whether cotton has entered the five true leaf stages, by This solves the current time-consuming, labor-intensive and inaccurate technical problems of manually judging the five true leaf stages of cotton

Images