Design of agaricus bisporus automatic grading system based on machine vision

Abstract

Aim at the agaricus bisporus postharvest automatic classification problem, this paper designed a kind of agaricus bisporus grading system based on machine vision, the system is mainly composed of machine vision system, mechanical system, automatic control system three parts, and analyzed the key technologies involved in every part. Extracted the feature parameters from the mushroom cap color, mushroom cap area and mushroom stem three aspects, combined with the classification standard, the final classification result is given by using edible fungus intelligent recognition platform, and then control the robot grabbing the agaricus bisporus into the corresponding classification box, the rate of accuracy reached over 88%. The results show that using machine vision based automatic grading system for the agaricus bisporus classification is feasible.