A NOVEL ALGORITHM for SPEEDING up KEYPOINT DETECTION and MATCHING

Jing Li, T. A.O. Yang, Quan Pan, Yong Mei Cheng, Jun Hou

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This work proposes a novel keypoint detector called QSIF (Quality and Spatial based Invariant Feature Detector). The primary contributions include: (1) a multilevel box filter is used to build the image scales efficiently and precisely, (2) by examining pixels in quality and spatial space simultaneously, QSIF can directly locate the keypoints without scale space extrema detection in the entire image spatial space, (3) QSIF can precisely control the number of output keypoints while maintaining almost the same repeatability of keypoint detection. This characteristic is essential in many real-time application fields. Extensive experimental results with images under scale, rotation, viewpoint and illumination changes demonstrate that the proposed QSIF has a stable and satisfied repeatability, and it can greatly speed up the keypoint detect and matching.

Original languageEnglish
Pages (from-to)643-661
Number of pages19
JournalInternational Journal of Image and Graphics
Volume8
Issue number4
DOIs
StatePublished - 1 Oct 2008

Keywords

  • image registration
  • Invariant feature
  • keypoint detection
  • keypoint matching

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