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Position-, rotation-, scale-, and orientation-invariant multiple object recognition from cluttered scenes

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journal contribution
posted on 2023-06-08, 07:48 authored by Peter Bone, Rupert YoungRupert Young, Chris ChatwinChris Chatwin
A method of detecting target objects in still images despite any kind of geometrical distortion is demonstrated. Two existing techniques are combined, each one capable of creating invariance to various types of distortion of the target object. A maximum average correlation height (MACH) filter is used to create invariance to orientation and gives good tolerance to background clutter and noise. A log r-? mapping is employed to give invariance to in-plane rotation and scale by transforming rotation and scale variations of the target object into vertical and horizontal shifts. The MACH filter is trained on the log r-? map of the target for a range of orientations and applied sequentially over regions of interest in the input image. Areas producing a strong correlation response can then be used to determine the position, in-plane rotation, and scale of the target objects in the scene.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Optical Engineering

ISSN

0091-3286

Publisher

Society of Photo-Optical Instrumentation Engineers

Issue

7

Volume

45

Page range

077203

Department affiliated with

  • Engineering and Design Publications

Research groups affiliated with

  • Industrial Informatics and Signal Processing Research Group Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

First Open Access (FOA) Date

2017-05-19

First Compliant Deposit (FCD) Date

2017-05-19

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