吉林大学学报（理学版）2016，Vol.54Issue(4)：862-866,5.DOI:10.13413/j.cnki.jdxblxb.2016.04.33
多特征筛选与支持向量机相融合的图像分类模型
Image Classification Model with Multiple Feature Selection and Support Vector Machine
摘要
Abstract
Aiming at the feature selection problem in image classification,we proposed a multiple feature selection and support vector machine for an image classification model.Firstly,we extracted a varity of features of the image and normalized the features.Secondly,we selected a set of optimal feature subset according to the average impact value of features.Finally,the multi classifier was built by using support vector machine,and the simulation experiments were carried out to verify the validity of the model by using image data set SIMPLIcity.The experimental results show that the proposed model can reduce the cost of image classification and improve the performance of image classification.关键词
图像处理/分类模型/多特征/支持向量机Key words
image processing/classification model/multiple feature/support vector machine分类
信息技术与安全科学引用本文复制引用
邓江洪,赵领..多特征筛选与支持向量机相融合的图像分类模型[J].吉林大学学报（理学版）,2016,54(4):862-866,5.基金项目
河南省科技攻关项目(批准号:132102210423 （）
122102210549) （）
