【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.更多还原

【Abstract】 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.更多还原