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A New Scheme for Keypoint Detection and Description

机译:关键点检测和描述的新方案

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摘要

The keypoint detection and its description are two critical aspects of local keypoints matching which is vital in some computer vision and pattern recognition applications. This paper presents a new scale-invariant and rotation-invariant detector and descriptor, coined, respectively, DDoG and FBRK. At first the Hilbert curve scanning is applied to converting a two-dimensional (2D) digital image into a one-dimensional (1D) gray-level sequence. Then, based on the 1D image sequence, an approximation of DoG detector using second-order difference-of-Gaussian function is proposed. Finally, a new fast binary ratio-based keypoint descriptor is proposed. That is achieved by using the ratio-relationships of the keypoint pixel value with other pixel of values around the keypoint in scale space. Experimental results show that the proposed methods can be computed much faster and approximate or even outperform the existing methods with respect to performance.
机译:关键点检测及其描述是局部关键点匹配的两个关键方面,这在某些计算机视觉和模式识别应用程序中至关重要。本文提出了一种新的尺度不变和旋转不变检测器和描述符,分别是DDoG和FBRK。首先,将希尔伯特曲线扫描应用于将二维(2D)数字图像转换为一维(1D)灰度序列。然后,基于一维图像序列,提出了使用二阶高斯差分函数的DoG检测器的近似方法。最后,提出了一种新的基于快速二进制比率的关键点描述符。这可以通过使用关键点像素值与比例空间中关键点周围其他值像素的比率关系来实现。实验结果表明,所提出的方法在性能上可以更快地计算,并且近似或优于现有方法。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第9期|310704.1-310704.10|共10页
  • 作者

    Yang Lian; Lu Zhangping;

  • 作者单位

    Hunan Univ Humanities, Dept Math Sci & Technol, Loudi 417000, Hunan, Peoples R China.;

    Jiangsu Univ, Coll Mech Engn, Zhenjiang 212013, Jiangsu, Peoples R China.;

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