Abstract：In order to better achieve the image retrieval based on semantics, the integrated features of color, texture and shape were used to represent the image and were also regarded as input vectors of Support Vector Machine (SVM). Through making study of image classes, the correlation from image low-level features to high-level semantics was built. The classification accuracy was improved by using comprehensive features. Then image library was organized by the semantic structure, and hierarchical representation of image semantics was realized. All keywords of different levels were combined to describe the semantic of images. The results show that the proposed method can make the image expressed by more comprehensive semantic in the case of getting good classification accuracy.
孔英会 苏亮. 基于层次语义的图像分类方法[J]. 计算机应用, 2011, 31(11): 3045-3047.
KONG Ying-hui SU Liang. Image classification method based on hierarchy semantics. Journal of Computer Applications, 2011, 31(11): 3045-3047.
2011, Vol. 31 
