文献类型：会议论文

英文题名：A novel perception based image categorization algorithm

作者：Yuan, Jia-Zheng[1]; Tian, Li-Yan[2]; Zhang, Rui-Zhe[3]; Huang, Jing-Hua[3]

第一作者：Yuan, Jia-Zheng

通讯作者：Yuan, J.-Z.

机构：[1] Institute of Information Technology, Beijing Union University, Beijing 100101, China; [2] College of Application Science and Technology, Beijing Union University, Beijing 100101, China; [3] Information Technology College, Beijing Union University, Beijing 100101, China

第一机构：北京联合大学智慧城市学院

通讯机构：[1]Institute of Information Technology, Beijing Union University, Beijing 100101, China|[1141734]北京联合大学智慧城市学院;[11417]北京联合大学;

会议论文集：PACIIA 2009 - 2009 2nd Asia-Pacific Conference on Computational Intelligence and Industrial Applications

会议日期：November 28, 2009 - November 29, 2009

会议地点：Wuhan, China

语种：英文

外文关键词：Artificial intelligence - Classifiers - Computation theory - Image retrieval - Imaging systems - Support vector machines - Topology

摘要：Image categorization plays an important role in the field of image retrieval and automatic annotation. Most existing algorithms adopted the low-level visual features to represent an image and the well-known Bag-of-words model followed by the SVM classifier was employed to fulfill the classification task. In this paper, instead of using the traditional low-level visual features, we employ the perception theory and propose a novel image categorization algorithm based on the representation of images' topological properties, i.e., an image can be represented by a low-dimensional features (e.g., Euler characteristic, the number of holes) which is called the topological properties. Given the new representations of images, a naive Bayes classifier is performed to fulfill the categorization task. The experimental results on the well-known image dataset show that based on the topological representation, the image categorization performance can be well improved. ?2009 IEEE.