| 余肖生,周宁,张芳芳.基于KNN的图像自动分类模型研究[J].中国图书馆学报,2007,33(1): |
| A KNN-Based Model for Automatic Image Categorization |
| 基于KNN的图像自动分类模型研究 |
| |
| DOI： |
| Key words:Automatic image categorization, K-nearest neighbor, Support vector machine, Bayes categorization |
| 中文关键词: 图像自动分类，K近邻算法，支持向量机，贝叶斯分类法 |
| 基金项目:本文系国家自然科学基金项目（70473068）和教育部社会科学研究重大课题攻关项目（05JZD0024）的研究成果之一. |
|
| Hits: 4620 |
| Download times: 3099 |
| Abstract: |
| Automatic image categorization is a process of categorizing images into defined categories by using automatic image categorisers. There arc many methods for the automatic categorization of images, among which the K-Nearest Neighbor algorithm is a case-based learning methyl and is a comparatively ideal automatic categorizer. On the basis of the K-Nearest Neighbor algorithm, the authors proposes a model for the automatic categorization of images, including the preprocessing, characteristic presentation, machine learning and categorization of images. 1 tab. 1 fig. 13 refs. |
| 中文摘要: |
| 所谓图像自动分类是指利用图像自动分类器把待分类的图像分配到预定义的图像类的过程。用于图像自动分类的方法有多种。其中K近邻算法是一种基于实例学习的方法，是一种较理想的自动分类器。本文在它的基础上提出了图像自动分类模型，整个图像自动分类过程包括图像预处理、特征表示、机器学习和图像分类4个步骤。表1。图1。参考文献13。 |
|
View Full Text
View/Add Comment Download reader |
