返回
Fast color-spatial feature based image retrieval methods
DOI:10.1016/j.eswa.2011.03.014.png)
摘要
En 中文
In this paper, three types of image features are proposed to describe the color and spatial distributions of an image. In these features, the K-means algorithm is adopted to classify all of the pixels in an image into several clusters according to their colors. By measuring the spatial distance among the pixels in a same cluster, the three types of color spatial distribution (CSD) features of the image is obtained. Based on the three types of CSD features, three image retrieval methods are also provided. To accelerate the image retrieval methods, a fast filter is also presented to eliminate most undesired images in advance. A genetic algorithm is also given to decide the most suitable parameters which are used in the proposed image retrieval methods. The proposed image retrieval methods are simple. Moreover, the experiments show that the proposed methods can provide impressive results as well. (C) 2011 Elsevier Ltd. All rights reserved.
Keyword:
Color-based image retrieval
Color-histogram
K-means
CBIR
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.5
论文数:
2.9W
被引数:
10.2W
机构
引用论文
Longitudinal transcriptome analyses show robust T cell immunity during recovery from COVID-19纵向转录组分析显示新型冠状病毒肺炎恢复过程中T细胞免疫功能强大

