吉林大学学报(理学版) ›› 2020, Vol. 58 ›› Issue (3): 627-633.

• 计算机科学 • 上一篇    下一篇

 空间颜色聚类算法及其在图像特征提取中的应用

李健1, 姜楠1, 宝音巴特2, 张帆3, 张伟健1, 王薇4   

  1. 1. 吉林农业大学 信息技术学院, 长春 130118; 2. 吉林省科学技术工作者服务中心, 长春 130021;
    3. 吉林农业大学 研究生院, 长春 130118; 4. 吉林农业大学 园艺学院, 长春 130118
  • 收稿日期:2019-07-22 出版日期:2020-05-26 发布日期:2020-05-20
  • 通讯作者: 李健 E-mail: liemperor@163.com

Spatial Color Clustering Algorithm and Its Applicationin Image Feature Extraction

LI Jian1, JIANG Nan1, BAOYIN Bate2, ZHANG Fan3, ZHANG Weijian1, WANG Wei4   

  1. 1. College of Information Technology, Jilin Agricultural University, Changchun 130118, China;
    2. Jilin Science and Technology Works Service Center, Changchun 130021, China;
    3. College of Graduate School, Jinlin Agricultural University; Changchun 130118, China;
    4. College of Horticulture, Jilin Agricultural University, Changchun 130118, China
  • Received:2019-07-22 Online:2020-05-26 Published:2020-05-20
  • Contact: LI Jian E-mail: liemperor@163.com

摘要: 针对目前图像基本颜色特征单一、 可提取信息不足的问题, 提出将图像进行HSV颜色空间转换, 先用均衡化直方图增强空间颜色互转后的图像空间
颜色像素, 再用融入rgb2ind的K-means均值聚类算法提亮均衡图像, 以增强图像颜色特征的提取目标和数量. 实验结果表明, 该方法优于普通空间颜色图像进行特征提取的效果, 实现了为颜色特征识别提供更多的检索信息.

关键词: HSV颜色空间, 均值聚类, 特征提取, 识别, 检索

Abstract: Aiming at the current problem of single basic color features of image and insufficient information available, we proposed to transform the image into HSV color space. We first used the equalization histogram to enhance the spatial color pixels of the image after the spatial color conversion, and then used K-means clustering algorithm integrated with rgb2ind to brighten the balanced image, so as to enhance the extraction target and quantity of image color feature. The experimental results show that the proposed method is better than that of the ordinary spatial color image for feature extraction, and provides more retrieval information for color feature recognition.

Key words:  , HSV color space, mean clustering, feature extraction, recognition, retrieval

中图分类号: 

  • TP399