基于数据挖掘的图像分类算法  

Image classification algorithm based on data mining

作　　者：唐普霞 石丽怡 TANG Puxia;SHI Liyi(Department of Public Safety Technology,Hainan Vocational College of Political Science and Law,Haikou 571100,China)

机构地区：[1]海南政法学院公共安全技术系,海南海口571100

出　　处：《现代电子技术》2017年第3期54-57,共4页Modern Electronics Technique

摘　　要：针对传统图像方法的分类精度难题,提出基于数据挖掘的图像分类算法。首先构建多媒体数据库中的图像检索信道模型,并进行向量量化编码,然后采用Harris角点检测算法提取图像特征点,并采用模糊C均值聚类算法实现图像分类。实验结果表明,该算法可以对图像内容信息进行准确的表达,提高了图像分类的精度,具有较强的鲁棒性。Aiming at the classification accuracy of the traditional image method,an image classification algorithm based on data mining is put forward. The image retrieval channel model of the multimedia database was constructed. The image was per?formed with vector quantization coding. The Harris corner detection algorithm is used to extract the feature points of the image.The fuzzy C?means clustering algorithm is adopted to classify the image. The experimental results show that the algorithm can ex?press the image content information accurately,improve the accuracy of the image classification,and has strong robustness.

关 键 词：数据挖掘 图像分类 特征提取 模糊C均值聚类 

分 类 号：TN911.73.34[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]