颜色特征的图像分类技术研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
3
期数:
2008年第2期
页码:
65-68
栏目:
学术论文—人工智能基础
出版日期:
2008-04-25
- Title:
- Image classification technology based on color features
- 关键词:
- 图像分类; 颜色特征; Boosting算法
- 分类号:
- TP391.41
- 文献标志码:
- A
- 摘要:
- 研究了基于颜色的图像特征对于图像分类结果的影响.给出了采用基于颜色位置分布特征进行分类的方法,并与基于RGB直方图特征和基于HSV直方图特征的方法进行了比较.分别采用随机森林、Boosting算法和MLP神经网络3种分类方法进行图像分类,建立了自然图像分类系统.基于实验结果比较了随机森林、Boosting算法和MLP神经网络3种分类方法的优缺点,发现Boosting算法表现最好,更加适合于图像分类.
- Abstract:
- This paper studies the effects of an image’s color features on image classification.We developed a new classification method based on positional distribution of colors and compare it with other methods based on RGB and HSV histograms.The random forest,the Boosting algorithm,and the MLP neural network were applied respectively to classify images and a natural image classification system built up.The advantages and disadvantages of these three classification algorithms are discussed according to experimental ...
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备注/Memo
国家自然科学基金资助项目(60773112);; 北京市自然科学基金资助项目(4082021)
更新日期/Last Update:
2008-08-26