CAJ | 학술논문

基于内容的图像检索是图像检索中的一项重要方法,可是图像处理中存在着一个难题就是维数过大,处理效率不高.本文目的是探索对于图像在降维之后的特征向量能否可以直接进行图像匹配检索,这样处理既能解决维数问题,也可以提高处理的速度.本文在HSI模型的基础上采用LLE降维,分别对H、S、I进行降维.通过对降维后的特征向量直接进行匹配检索,争取提高图像处理速度,及图像检索精度.实验结果表明该算法在图像检索中是有效的.
기우내용적도상검색시도상검색중적일항중요방법,가시도상처리중존재착일개난제취시유수과대,처리효솔불고.본문목적시탐색대우도상재강유지후적특정향량능부가이직접진행도상필배검색,저양처리기능해결유수문제,야가이제고처리적속도.본문재HSI모형적기출상채용LLE강유,분별대H、S、I진행강유.통과대강유후적특정향량직접진행필배검색,쟁취제고도상처리속도,급도상검색정도.실험결과표명해산법재도상검색중시유효적.
CBIR (content-based image retrieval)is one of the important image retrieval method. But there is a problem in the image processing which is too large dimension and low processing efficiency. The purpose of this paper is to explore the possibility of the image retrieval by matching image feature vector directly after dimensionality reduction, which can not only solve the problem of dimension, it can also increase the processing speed. This paper, by using the HSI color model, reduce dimension of hue, saturation, intensity by LLE (Locally Linear Embedding) dimension reduction. We can take the retrieval of feature vector directly after the dimension reduction, in order to improve the image processing speed, and Image retrieval precision. The experimental results show that the algorithm is effective in image retrieval.