The Study of Image Feature Extraction and Classification

被引:0
作者
Guo, Jingjin [1 ]
Liu, Lizhen [1 ]
Song, Wei [1 ]
Du, Chao [1 ]
Zhao, Xinlei [2 ]
机构
[1] Capital Normal Univ, Informat & Engn Coll, Beijing 100048, Peoples R China
[2] Capital Normal Univ, Foreign Language Coll, Beijing 100048, Peoples R China
来源
PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC 2017) | 2017年
基金
美国国家科学基金会;
关键词
feature extraction; logistic regression; SVM; image classification;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As we all know, research continues in the areas of image classification development in computer vision. People eagerly hope to achieve a perfect classification accuracy, however, many results of these experiments are less than satisfactory because of many complex factors. Therefore, in order to find these factors and improve the classification accuracy, we describe the details of classification methods with logistic regression and support vector machine algorithm, then discuss the impact of different methods on classification results and the factors that affect the classification accuracy in one method. Before that we briefly introduce the image feature extraction which plays a necessary role of image classification.
引用
收藏
页码:174 / 178
页数:5
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