Adaptive image matching using discrimination of deformable objects

Insu Won; Jaehyup Jeong; Hunjun Yang; Jangwoo Kwon; Dongseok Jeong

doi:10.3390/sym8070068

Adaptive image matching using discrimination of deformable objects

Insu Won, Jaehyup Jeong, Hunjun Yang, Jangwoo Kwon, Dongseok Jeong

Inha University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

We propose an efficient image-matching method for deformable-object image matching using discrimination of deformable objects and geometric similarity clustering between feature-matching pairs. A deformable transformation maintains a particular form in the whole image, despite local and irregular deformations. Therefore, the matching information is statistically analyzed to calculate the possibility of deformable transformations, and the images can be identified using the proposed method. In addition, a method for matching deformable object images is proposed, which clusters matching pairs with similar types of geometric deformations. Discrimination of deformable images showed about 90% accuracy, and the proposed deformable image-matching method showed an average 89% success rate and 91% accuracy with various transformations. Therefore, the proposed method robustly matches images, even with various kinds of deformation that can occur in them.

Original language	English
Article number	68
Journal	Symmetry
Volume	8
Issue number	7
DOIs	https://doi.org/10.3390/sym8070068
State	Published - 2016

Bibliographical note

Publisher Copyright:
© 2016 by the authors.

Keywords

Discrimination of deformable object
Image matching
Matching-pair clustering

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10.3390/sym8070068

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title = "Adaptive image matching using discrimination of deformable objects",

abstract = "We propose an efficient image-matching method for deformable-object image matching using discrimination of deformable objects and geometric similarity clustering between feature-matching pairs. A deformable transformation maintains a particular form in the whole image, despite local and irregular deformations. Therefore, the matching information is statistically analyzed to calculate the possibility of deformable transformations, and the images can be identified using the proposed method. In addition, a method for matching deformable object images is proposed, which clusters matching pairs with similar types of geometric deformations. Discrimination of deformable images showed about 90% accuracy, and the proposed deformable image-matching method showed an average 89% success rate and 91% accuracy with various transformations. Therefore, the proposed method robustly matches images, even with various kinds of deformation that can occur in them.",

keywords = "Discrimination of deformable object, Image matching, Matching-pair clustering",

author = "Insu Won and Jaehyup Jeong and Hunjun Yang and Jangwoo Kwon and Dongseok Jeong",

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journal = "Symmetry",

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T1 - Adaptive image matching using discrimination of deformable objects

AU - Won, Insu

AU - Jeong, Jaehyup

AU - Yang, Hunjun

AU - Kwon, Jangwoo

AU - Jeong, Dongseok

PY - 2016

Y1 - 2016

N2 - We propose an efficient image-matching method for deformable-object image matching using discrimination of deformable objects and geometric similarity clustering between feature-matching pairs. A deformable transformation maintains a particular form in the whole image, despite local and irregular deformations. Therefore, the matching information is statistically analyzed to calculate the possibility of deformable transformations, and the images can be identified using the proposed method. In addition, a method for matching deformable object images is proposed, which clusters matching pairs with similar types of geometric deformations. Discrimination of deformable images showed about 90% accuracy, and the proposed deformable image-matching method showed an average 89% success rate and 91% accuracy with various transformations. Therefore, the proposed method robustly matches images, even with various kinds of deformation that can occur in them.

AB - We propose an efficient image-matching method for deformable-object image matching using discrimination of deformable objects and geometric similarity clustering between feature-matching pairs. A deformable transformation maintains a particular form in the whole image, despite local and irregular deformations. Therefore, the matching information is statistically analyzed to calculate the possibility of deformable transformations, and the images can be identified using the proposed method. In addition, a method for matching deformable object images is proposed, which clusters matching pairs with similar types of geometric deformations. Discrimination of deformable images showed about 90% accuracy, and the proposed deformable image-matching method showed an average 89% success rate and 91% accuracy with various transformations. Therefore, the proposed method robustly matches images, even with various kinds of deformation that can occur in them.

KW - Discrimination of deformable object

KW - Image matching

KW - Matching-pair clustering

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U2 - 10.3390/sym8070068

DO - 10.3390/sym8070068

M3 - Article

AN - SCOPUS:85008144352

SN - 2073-8994

VL - 8

JO - Symmetry

JF - Symmetry

IS - 7

M1 - 68

ER -

Adaptive image matching using discrimination of deformable objects

Abstract

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