Detection of Agricultural Microbial Colonies Based on Image Morphology and Otsu Method

  • Xiaoyu Xu
Keywords: Agriculture Microorganism, Intelligent Irrigation, Image Morphology, Otsu Method

Abstract

Microorganism has played an important role in the health, growth and development of agricultural animals and plants, the improvement and restoration of water, soil and atmospheric environment. So to learn about the impact of microorganism on agricultural production activities, the approaches it exerts the effect, and the regulation of plant-related microbial community structure is of great significance to enhance the applications of microorganism in agricultural production and then increase crop yield, save relevant costs, and promote the development of green agriculture and eco-agriculture.According to the information of microbial colonies, it can also realize timely and appropriate intelligent irrigation for farmland, and play an important role in the growth of crops and the construction of intelligent agriculture.This paper proposes the method for detecting agricultural microbial colonies based on image morphology and Otsu algorithm. This method, mainly based on the determination result of a single frame of image in the video of colonies of agriculture microorganisms and the related information of continuous video frames, records different key states at different moments and in different spaces, and through the switch of different key states, maximizes all environment information obtained in order for accurate detection, tracking and counting statistics of microbial colony target.It demarcates all possible targets detected in every frame of image, proceeds multi-frame tracking on every target, and combines with the results of follow-up frames for comparison. Every target object must go through confirmation of different states, including detection state, storage state, foreground extraction state, statistic state, deletion state and display state, so as toremoveinaccurate detection targets, preserve, track and count the accurate ones. The simulation experiment proves that this method is effective.

Published
2020-06-01