D_S_2006_peter_bone_paper.pdf (484.19 kB)
Position-, rotation-, scale-, and orientation-invariant multiple object recognition from cluttered scenes
journal contribution
posted on 2023-06-08, 07:48 authored by Peter Bone, Rupert YoungRupert Young, Chris ChatwinChris ChatwinA 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 EngineeringISSN
0091-3286Publisher
Society of Photo-Optical Instrumentation EngineersExternal DOI
Issue
7Volume
45Page range
077203Department 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
2012-02-06First Open Access (FOA) Date
2017-05-19First Compliant Deposit (FCD) Date
2017-05-19Usage metrics
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