Research on The Precision Seeding System for Tiny Particle Seed Based on Machine Vision

Abstract

A detection algorithm with machine vision that can quickly identify the number of seed particles is proposed by comparing the standard image templates with capture images. The online identification sorting system for small particles of seeds is designed based on machine electrical integration technology. The precise concern area is set up for the acquired image using image mask function. The image noise interference is reduced through the methods that include the image look-up table function, gray value erosion and dilation processing of morphology. The geometric features template previously divided that is carrot Seed image is searched to determine whether such a template is existed. The shape detection and image parameters output for particle image are conducted to determine the number of seed particles by using particle analysis function. High-speed solenoid valve is controlled by PLC (Programmable Logic Controller) to select seeds exactly and the package is carried out using seeds weaving technology. The seed single hole rate can be reached more than 92%.