Kernel-Based Image Retrieval with Ontology

摘要：

Due to the huge increase in the amount of digital images available in the explosive Internet era, making efficient Content Based Image Retrieval (CBIR) systems has become one of the major endeavors. In this paper, the authors study the integration of subsequence kernel function based on ontology. Using the VSM to create subsequence kernels, The kernel methodology described here not only overcome the VSM ignoring any semantic relation between words, but also result both in functional similarity and in sequence/words similarity by gap-weighted subsequences kernels, and semantic character is also taken into account. Experiments show that the method has more exact retrieval results, and its cost is under the accepted tolerance.

关键词： subsequence kernel onotology image retrieval gap-weighted

作者: Pang Shuxia Yuan Zhanting Zhang Qiuyu Li Rui

作者单位: School of Computer and Communication Lanzhou University of Science and Technology Lanzhou, China

会议类型: 国际会议

会议名称: 2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)

会议地点: 太原

会议语种:英文

页码: 213-216

在线出版日期: 2009-07-10（万方平台首次上网日期，不代表论文的发表时间）