CAJ | 학술논문

基于关键字和基于内容的图像检索是图像检索系统中的两种重要方法.而当今,图像检索系统重点强调在图像检索过程中,高层语义与低层视觉特征的结合.最近,一些研究者在检索周期中采用用户互交,使用上述方法和半自动图像检索的结合,取得了一些成果,但没有自学习的动态语义功能,检索效率不高.论文给出的方法是基于一个分层的语义网络,在图像检索领域能够响应不能的需求,并且根据用户的反馈,执行一个新的动态学习检索过程,可以明显的提高图像检索效率.
기우관건자화기우내용적도상검색시도상검색계통중적량충중요방법.이당금,도상검색계통중점강조재도상검색과정중,고층어의여저층시각특정적결합.최근,일사연구자재검색주기중채용용호호교,사용상술방법화반자동도상검색적결합,취득료일사성과,단몰유자학습적동태어의공능,검색효솔불고.논문급출적방법시기우일개분층적어의망락,재도상검색영역능구향응불능적수구,병차근거용호적반궤,집행일개신적동태학습검색과정,가이명현적제고도상검색효솔.
Content-based image retrieval and text-based image retrieval are two Fundamental approaches in the field of image retrieval. Nowadays,image retrieval systems,emphasize the combining of high level semantics and low level visual features in the image indexing process. Recently, the researchers use the combining approaches and semiautomatic image retrieval, using the user interaction in the retrieval cycle. The proposed approach can reply different requests in the image retrieval domain based on a hierarchical semantic network and doing a new kind of learning process by the feedbacks given by user.