基于对象语义的图像分割和分类方法  

Appoach To Object Semanteme Based Image Segmentation and Classification

作　　者：徐驰[1] 徐燕凌[1] 

机构地区：[1]同济大学软件学院,上海201804

出　　处：《重庆大学学报（自然科学版）》2006年第8期98-101,共4页Journal of Chongqing University

摘　　要：提出一种基于对象语义的图像分割和分类方法.建立多层级区域生长算法HRGSeg对图像进行分割,从而去除“弱对象语义”细节,降低过度分割的影响.在此基础上,提取颜色、边缘、纹理等低层次特征作为特征向量,并利用支持向量机建立样本训练机制,实现低层次特征向高层对象语义的映射.实验中,采用层次化分类机制,取得了较理想的结果.There exist potential problems in current region-based image retrievals. This paper proposes a novel approach to object semanteme based image segmentation and classification. First, a hierarchical region growing image segmentation is established using HRGSeg algorithm, which can effectively get rid of weak object semantemes and play down the side effect of over-segmentation. Based on it, low-level features like color, edge and texture are extracted mapped into high-level object semantics hierarchically by using SVM. A fairly good experiment result is achieved and shows the feasibility of our approach.

关 键 词：对象语义 图像分割 支持向量机 语义分类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]