It is very important to improve the quality and high yield of rice by adjusting the light, temperature and humidity in the environment of seedling development. This paper proposed a method for recognizing seedling development status based on machine vision algorithm for rice seedlings under the condition that the monitoring of rice seedlings was out of time caused by monitoring. It studied on the seedling of Dongnong426 and Dongnong428 by rice thermotank, on seedling RGB color image segmentation using the covariance clustering algorithm, then used continuous corrosion pretreatment open operation combined with Hough transform. According to the information extraction and morphological parameters of leggy seedlings directly related, such as plant height, leaf area, horned, growth rate, curve fitting, the results would be displayed on the interface of the software. The test results show that the method can correctly identify and accurately extract the morphological parameters of seedlings, the accuracy rate is 87.5%, the morphological parameter identification error is less than 7%, this method provides an effective reference for the research of rice seedling sports factory.

[2019-05-05] Printed Article /doc/2017.12.0837/v2