A theory of phase singularities for image representation and its applications to object tracking and image matching

Yu Qiao, Wei Wang, Nobuaki Minematsu, Jianzhuang Liu, Mitsuo Takeda, Xiaoou Tang

Research output: Contribution to journalArticle

Abstract

This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods. © 2009 IEEE.

Original languageEnglish
Pages (from-to)2153-2166
Number of pages14
JournalIEEE Transactions on Image Processing
Volume18
Issue number10
DOIs
Publication statusPublished - 2009

Fingerprint

Image matching
Image analysis

Keywords

  • Image matching
  • Image representation
  • Object tracking
  • Phase singularity
  • Scale space
  • Transformation invariance

Cite this

Qiao, Yu ; Wang, Wei ; Minematsu, Nobuaki ; Liu, Jianzhuang ; Takeda, Mitsuo ; Tang, Xiaoou. / A theory of phase singularities for image representation and its applications to object tracking and image matching. In: IEEE Transactions on Image Processing. 2009 ; Vol. 18, No. 10. pp. 2153-2166.
@article{5e5d0b1ec5cc4ab7a7215e4ec08de51e,
title = "A theory of phase singularities for image representation and its applications to object tracking and image matching",
abstract = "This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods. {\circledC} 2009 IEEE.",
keywords = "Image matching, Image representation, Object tracking, Phase singularity, Scale space, Transformation invariance",
author = "Yu Qiao and Wei Wang and Nobuaki Minematsu and Jianzhuang Liu and Mitsuo Takeda and Xiaoou Tang",
year = "2009",
doi = "10.1109/TIP.2009.2026623",
language = "English",
volume = "18",
pages = "2153--2166",
journal = "IEEE Transactions on Image Processing",
issn = "1057-7149",
publisher = "IEEE",
number = "10",

}

A theory of phase singularities for image representation and its applications to object tracking and image matching. / Qiao, Yu; Wang, Wei; Minematsu, Nobuaki; Liu, Jianzhuang; Takeda, Mitsuo; Tang, Xiaoou.

In: IEEE Transactions on Image Processing, Vol. 18, No. 10, 2009, p. 2153-2166.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A theory of phase singularities for image representation and its applications to object tracking and image matching

AU - Qiao, Yu

AU - Wang, Wei

AU - Minematsu, Nobuaki

AU - Liu, Jianzhuang

AU - Takeda, Mitsuo

AU - Tang, Xiaoou

PY - 2009

Y1 - 2009

N2 - This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods. © 2009 IEEE.

AB - This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods. © 2009 IEEE.

KW - Image matching

KW - Image representation

KW - Object tracking

KW - Phase singularity

KW - Scale space

KW - Transformation invariance

U2 - 10.1109/TIP.2009.2026623

DO - 10.1109/TIP.2009.2026623

M3 - Article

VL - 18

SP - 2153

EP - 2166

JO - IEEE Transactions on Image Processing

JF - IEEE Transactions on Image Processing

SN - 1057-7149

IS - 10

ER -