Distortion processing in image matching problems

C. M. Wu, R. M. Owens, Mary Jane Irwin

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

An image-matching algorithm, called the dynamic space-warping algorithm (DSWA), is presented. It is based on both local-distance diagrams and dynamic programming. The DSWA can solve space-warping problems (e.g., shrinking, enlarging, rotation, and distortion) with good performance by embedding controllable flexibility (or warping). The concept of flexibility can be explained using local-distance diagrams. With flexibility, the local-distance diagram between two two-dimensional images is four dimensional. Based on compression and expansion, DSWA generates a minimum distance from the four-dimensional local-distance diagram. Experimental results show that the DSWA is very reliable.

Original languageEnglish (US)
Pages (from-to)2181-2184
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
StatePublished - Dec 1 1990
Event1990 International Conference on Acoustics, Speech, and Signal Processing: Speech Processing 2, VLSI, Audio and Electroacoustics Part 2 (of 5) - Albuquerque, New Mexico, USA
Duration: Apr 3 1990Apr 6 1990

Fingerprint

Image matching
diagrams
Processing
flexibility
dynamic programming
expansion
programming
Dynamic programming
embedding

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

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abstract = "An image-matching algorithm, called the dynamic space-warping algorithm (DSWA), is presented. It is based on both local-distance diagrams and dynamic programming. The DSWA can solve space-warping problems (e.g., shrinking, enlarging, rotation, and distortion) with good performance by embedding controllable flexibility (or warping). The concept of flexibility can be explained using local-distance diagrams. With flexibility, the local-distance diagram between two two-dimensional images is four dimensional. Based on compression and expansion, DSWA generates a minimum distance from the four-dimensional local-distance diagram. Experimental results show that the DSWA is very reliable.",
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Distortion processing in image matching problems. / Wu, C. M.; Owens, R. M.; Irwin, Mary Jane.

In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 4, 01.12.1990, p. 2181-2184.

Research output: Contribution to journalConference article

TY - JOUR

T1 - Distortion processing in image matching problems

AU - Wu, C. M.

AU - Owens, R. M.

AU - Irwin, Mary Jane

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N2 - An image-matching algorithm, called the dynamic space-warping algorithm (DSWA), is presented. It is based on both local-distance diagrams and dynamic programming. The DSWA can solve space-warping problems (e.g., shrinking, enlarging, rotation, and distortion) with good performance by embedding controllable flexibility (or warping). The concept of flexibility can be explained using local-distance diagrams. With flexibility, the local-distance diagram between two two-dimensional images is four dimensional. Based on compression and expansion, DSWA generates a minimum distance from the four-dimensional local-distance diagram. Experimental results show that the DSWA is very reliable.

AB - An image-matching algorithm, called the dynamic space-warping algorithm (DSWA), is presented. It is based on both local-distance diagrams and dynamic programming. The DSWA can solve space-warping problems (e.g., shrinking, enlarging, rotation, and distortion) with good performance by embedding controllable flexibility (or warping). The concept of flexibility can be explained using local-distance diagrams. With flexibility, the local-distance diagram between two two-dimensional images is four dimensional. Based on compression and expansion, DSWA generates a minimum distance from the four-dimensional local-distance diagram. Experimental results show that the DSWA is very reliable.

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