CAJ | 학술논문

为了解决图像检索以及遥感图像识别等图像处理研究中本质的问题——如何对高层抽象图像语义进行有效的分类,本文采用生物视觉认知机理,结合生物特征信息,用最小生成树的方法构造图像信息语义树,提出了一个基于稀疏编码的图像语义分类器(SCISC)的模型。实验结果表明:该模型在图像分类中有较高正确率。
위료해결도상검색이급요감도상식별등도상처리연구중본질적문제——여하대고층추상도상어의진행유효적분류,본문채용생물시각인지궤리,결합생물특정신식,용최소생성수적방법구조도상신식어의수,제출료일개기우희소편마적도상어의분류기(SCISC)적모형。실험결과표명:해모형재도상분류중유교고정학솔。
In order to solve the problem in the image process researches,it is very important to find an efficient,biologic recognition related,and high-level semantic image classification method.By adopting the theories of biologic visual recognition and knowledge engineering combined with biologic characteristic(information,) and using minimum spanning tree as an image information construction tree,this paper pre-(sents) a sparse coding-based image semantic classifier (SCISC) model.The experimental result shows that...