首页> 外文期刊>Connection Science >Content-based image retrieval using block truncation coding based on edge quantization
【24h】

Content-based image retrieval using block truncation coding based on edge quantization

机译:基于内容的图像检索,使用基于边缘量化的块截断编码

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper, we propose an effective image retrieval approach using block truncation coding compressed data stream based on edge-based quantization (EQBTC). First, an image is compressed into corresponding quantisers and a bitmap image by EQBTC. Then, the quantisers are used for colour feature extraction, whereby the bitmap image and grey image are used for luminance and edge feature extraction. Subsequently, two image features, the colour histogram feature (CHF) and the overall structure feature (OSF), are computed to measure the similarity between two images using a specific distance metric computation. The results presented in this paper demonstrate that the proposed model is superior to the block truncation coding image retrieval scheme and some earlier proposed methods.
机译:在本文中,我们提出了一种基于边缘的量化(EQBTC)的块截断编码压缩数据流的有效图像检索方法。首先,通过EQBTC压缩成对应的量程器和位图图像的图像。然后,量子器用于彩色特征提取,由此位图图像和灰度图像用于亮度和边缘特征提取。随后,计算两个图像特征,颜色直方图特征(CHF)和整体结构特征(OSF),以测量使用特定距离度量计算的两个图像之间的相似性。本文提出的结果表明,所提出的模型优于块截断编码图像检索方案和一些前面提出的方法。

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