Classification model of seed cotton grade based on least square support vector machine regression method

Abstract

Grade classification of seed cotton is a major problem that has an significant impact on the agricultural economy. According to characteristics like impurities, yellowness and brightness that extract from images of seed cotton, constructing classification model of seed cotton base on the least square method. Using support vector machine regression to come up with a well improved algorithm. After full learning, seed cotton classification accuracy satisfy the actual application needs.