Paper
30 September 1996 Invariant image recognition by neural networks and modified moment invariants
Dayong Wang, Weixing Xie
Author Affiliations +
Abstract
In this paper, a neural networks based approach for distortion invariant image recognition is presented. To reduce the dimension of the required networks, as well as to achieve invariancy, six distortion-invariant feature are extracted from each image and are used as inputs to the neural networks. These six features are derived from the modified geometrical moments of the image, which are calculated through a corrected discrete formula for computing moments more accurately. A multilayer perceptron network trained by the back-propagation algorithm can carry out the classification based on the above features. Experimental results on industrial tools and character recognition are to be given.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dayong Wang and Weixing Xie "Invariant image recognition by neural networks and modified moment invariants", Proc. SPIE 2898, Electronic Imaging and Multimedia Systems, (30 September 1996); https://doi.org/10.1117/12.253401
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Neural networks

Binary data

Detection and tracking algorithms

Error analysis

Pattern recognition

Feature extraction

Image classification

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