首页> 外文期刊>Neurocomputing >Computing invariants of Tchebichef moments for shape based image retrieval
【24h】

Computing invariants of Tchebichef moments for shape based image retrieval

机译:计算基于形状的图像检索的Tchebichef矩不变量

获取原文
获取原文并翻译 | 示例

摘要

Generally, discrete orthogonal moments are difficult to induce rotation invariants. Based on relationship between Tchebichef polynomials and power series, we propose a new algorithm to compute rotation invariants of Tchebichef moments. The translation and scale invariants of Tchebichef moments are achieved by pre-normalizing the image to a standard image. Selected invariants of Tchebichef moments form a new effective shape feature for image retrieval. The retrieval performance of the proposed descriptor is compared with radial Tchebichef moment invariants and two kinds of Zernike moment invariants. Retrieval experiment results show that the proposed shape feature is robust to deformations generated by image shape rotation and scaling. (C) 2016 Elsevier B.V. All rights reserved.
机译:通常,离散正交矩很难引起旋转不变性。基于Tchebichef多项式与幂级数之间的关系,我们提出了一种新的算法来计算Tchebichef矩的旋转不变量。通过将图像预先归一化为标准图像,可以实现Tchebichef矩的平移和尺度不变性。 Tchebichef矩的选定不变量形成用于图像检索的新有效形状特征。将所提出的描述符的检索性能与径向Tchebichef矩不变量和两种Zernike矩不变量进行比较。检索实验结果表明,所提出的形状特征对于由图像形状旋转和缩放产生的变形具有鲁棒性。 (C)2016 Elsevier B.V.保留所有权利。

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