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author:

Huang, Liqin (Huang, Liqin.) [1] | Chen, Caigan (Chen, Caigan.) [2] | Shen, Henghua (Shen, Henghua.) [3] | He, Bingwei (He, Bingwei.) [4]

Indexed by:

EI

Abstract:

SURF (Speeded-Up Robust Features) overcomes the expensive computation of SIFT (Scale Invariant Feature Transform), but both of them are designed mainly for gray-scale images. To overcome this drawback, color information could be added in the registration. This paper presents a novel adaptive registration algorithm of color images based on the SURF descriptor. Firstly, key points and descriptors are calculated using SURF. Secondly, color information is superimposed upon the key points' descriptor to construct a modified descriptor. Finally, a two-way matching method based on adaptive Euclidean nearest/second nearest discrimination law is designed for image matching. Extensive experimental evaluations show that the algorithm not only inherits the superior performance of the SURF algorithm, but also increases adaptive matching capability for color images. © 2015 Elsevier Ltd. All rights reserved.

Keyword:

Color Color matching

Community:

  • [ 1 ] [Huang, Liqin]School of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 2 ] [Chen, Caigan]School of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 3 ] [Shen, Henghua]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [He, Bingwei]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • [he, bingwei]school of mechanical engineering and automation, fuzhou university, fuzhou, china

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Source :

Measurement: Journal of the International Measurement Confederation

ISSN: 0263-2241

Year: 2015

Volume: 66

Page: 118-124

1 . 7 4 2

JCR@2015

5 . 2 0 0

JCR@2023

ESI HC Threshold:183

JCR Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 42

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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