Abstract:
This paper proposes uses gradient histogram and color histogram as classification feature to analyze the difference between Least Square-Support Vector Machine(LS-SVM) algorithm and Support Vector Machine(SVM) algorithm. It compares the LS-SVM algorithm with several traditional algorithms and introduces LS-SVM algorithm into image spam filtering. Experimental results show that the method can improve the detection rate of image spam.
Key words:
image spam,
Least Square-Support Vector Machine(LS-SVM),
Support Vector Machine(SVM)
classification feature
摘要: 提出以图像的梯度直方图和颜色直方图作为分类特征,分析最小二乘支持向量机(LS-SVM)算法以及该算法与传统SVM算法的区别,比较传统分类算法与LS-SVM算法的分类准确度,将LS-SVM算法用于图像垃圾邮件过滤。实验结果表明,该方法能提高图像垃圾邮件的检测率。
关键词:
图像垃圾邮,
最小二乘支持向量机,
支持向量机,
分类特征
CLC Number:
LIU Fen, SHUAI Jian-Mei. Image Spam Filtering Based on Gradient and Color Feature[J]. Computer Engineering, 2010, 36(16): 157-160.
刘芬, 帅建梅. 基于梯度和颜色特征的图像垃圾邮件过滤[J]. 计算机工程, 2010, 36(16): 157-160.