基于对象语义的图像分割和分类方法

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．

Appoach To Object Semanteme Based Image Segmentation and Classification

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.