【24h】

Content-based image retrieval using new color histogram

机译:使用新的颜色直方图的基于内容的图像检索

获取原文

摘要

This study has proposed a new method of color representation, and a method of similarity measurement in order to overcome the disadvantages of a color histogram. The existing color histogram intersection method uses only the frequency value of the same color, after color quantization; which causes quantization errors. To reduce this error, it calculated the mean value of RGB color components and color frequency in each color region, selected them as the representative value of the similar region of a relevant color, then stored this in the DB as a feature vector, and finally, measured the similarity between color images by applying fuzzy theory. As a result, the color histogram has retrieved similarity between images more precisely than the existing method did. The study experimented on 1,000 color images by the new color histogram retrieval method, and found it more precise than the existing method.
机译:这项研究提出了一种新的颜色表示方法和一种相似度测量方法,以克服颜色直方图的缺点。现有的颜色直方图相交方法在对颜色进行量化后仅使用相同颜色的频率值。这会导致量化误差。为了减少该误差,它计算了每个颜色区域中RGB颜色分量的平均值和颜色频率,选择它们作为相关颜色相似区域的代表值,然后将其作为特征向量存储在DB中,最后运用模糊理论测量了彩色图像之间的相似度。结果,与现有方法相比,颜色直方图更精确地检索了图像之间的相似性。该研究使用新的颜色直方图检索方法对1,000幅彩色图像进行了实验,发现它比现有方法更精确。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号