Study Of Corn Species Identification Based On Digital Image Processing

Along with the development of information technique, digital image processing and identifying technology becomes a vital one in inspecting the quality of seed by computer. The main purpose of this paper is to deeply research the corn species identification mainly by computer image processing technology. As well this paper involves in other knowledges such as photograph, optics, plant physiology, chroma, pattern recognition etc.First, the main contents of the paper are as follows:1. The image of corn seed collectionThe method of shooting image is researched on to advance the identification accuracy by computer and reduce restrictive conditions when collect image. Zhengdan958, Liaodan565, Jingke25 which are in common use in this region are selected as the researched objects. This paper analyzes their images which are obtained under different conditions.2. The image of corn seed pre-processParttioning Background: This paper decides to adopt iterative method through starting experiment by a few partition methods and comparing the experiment results.Smoothing image: After parttioning background, there are same isolated noise points in the image. By consulting datum, self-adjusing median filter is adopted to smoothing image.Correcting color: A method is found out in the research that correct image color according to the color of the standard whiteboard. Using the method to correct color improves the accuracy of corn seed color in the image.Seed separation: Standard whiteboard and separate seeds are distilled Mainly by labeling area method.3. The characteristic of corn seed pick-upIn addition to a few general characteristics about color, shape and size. This paper finds out the ratio of white part(embryo) and yellow part(crown) of corn seed and their shapes are useful. Then, by deeply researching in this aspect, new characteristics such as the size of the two parts and the color of the yellow part are picked up. RGB model and HSV model are combined together during picking up the color characteristics.4. The character of corn seed optimization and the value of new characteristics validationThis paper uses support vector machine (SVM) combined with genetic algorithm(GA) to discriminatively optimize new characteristics and general characteristics to validate the value of the new characteristic. The recognition rates of the two best character and the select rates of characteristics approve that some new characteristics are very useful. Through analyzing data of the ratio of white part and yellow part, the value of the characteristic are further confirmed. By experimentalizing, the color characteristics of the yellow area are better than the whole corn seed's to the species identification.5. The corn species identificationUsing Support Vector Machine to identify the breed of corn seed, the separate rates are 90.1%, 93.5%, 96%.Second, the innovative aspects of this paperImages of corn seeds are obtained out of fixed illuminate room and a simple and useful method of color correction is put forward which accelerates the identification process to get away from laboratory. And that some characteristics which are found out by partitioning the corn seed to white part and yellow part are valuable to the identification.