Abstract
Corn is one of the most important grains in the world, and it is wide cultivation. Corn varieties are numerous, but how to quickly identify the varieties is a problem. With the development of machine vision, automatic identification technology is gradually applied to the analysis of corn varieties. This article introduces an image acquisition system which collects and processes the pictures of corn grain. It contains an experiment box for collecting pictures and a computer which processes the pictures with Matlab. The experiment box includes main light source, auxiliary light source, a lifter that could adjust the distance of the object and the camera lens and a stage which held the corn grain. Pictures of corn grain were collected by digital camera. Taking the characteristics of shape and colour as the research object, this paper researches how to place the auxiliary light source and how to set the light intensity when the lifter was fixed, and how to set the distance when determining the light source. Experimental results show that, the light spot which came from camera flash affected feature extraction, the auxiliary light source should be placed in the form of parallel or vertical, and the distance of object to the camera lens within the scope of twenty-six to thirty-one centimetres is better.
