Fast color-spatial feature based image retrieval methods
Fast color-spatial feature based image retrieval methods
复制标题
DOI：
10.1016/j.eswa.2011.03.014
复制
发表时间：
2011-09
期刊：
影响因子：
--
通讯作者：
Chuen-Horng Lin;Der-Chen Huang;Y. Chan;Kai-Hung Chen;Yen-Jen Chang
中科院分区：
文献类型：
--
作者：
Chuen-Horng Lin;Der-Chen Huang;Y. Chan;Kai-Hung Chen;Yen-Jen Chang
本文提出了三种图像特征来描述图像的颜色和空间分布。在这些特征中，采用K-means算法将图像中的所有像素根据其颜色分为几个簇。通过测量同一类像素之间的空间距离，得到图像的三种颜色空间分布（CSD）特征。基于这三种CSD特征，本文提出了三种图像检索方法。为了加快图像检索的速度，本文还提出了一种快速过滤器，可以预先去除大部分不需要的图像。并给出了一种遗传算法来确定最合适的参数，用于所提出的图像检索方法。提出的图像检索方法简单。此外，实验表明，所提出的方法也可以提供令人印象深刻的结果。
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.