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15 October 1986 Shift-Invariant Recognition Of Rotationatly Deformed Ship Silhouettes At Multiple Resolution Scales
Mark S. Schmalz, Frank M. Caimi
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Proceedings Volume 0638, Hybrid Image Processing; (1986) https://doi.org/10.1117/12.964279
Event: 1986 Technical Symposium Southeast, 1986, Orlando, United States
Abstract
A novel method for two-dimensional pattern recognition and feature extraction, applicable to microprocessor-based vision systems, is presented which employs fractal geometric analysis. Fractal contour transformation and transform correlation techniques are discussed in relation to their effectiveness in classifying rotationally deformed images over a wide resolution range. vractal geometric analysis exhibits several attributes: 1. position-, size-, and rotation-invariance is preserved in the absence of image coordinate transformation, 2. invariance to out-of-plane rotation is exhibited over the range ±60° of broadside, and 3. out-of-plane rotation can be computed from imagery and quantified in terms of the fractal dimension. This work is supported by experimental verification of a ship silhouette recognition algorithm. Results are presented in terms of recognition ratio and computational load.
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Mark S. Schmalz and Frank M. Caimi "Shift-Invariant Recognition Of Rotationatly Deformed Ship Silhouettes At Multiple Resolution Scales", Proc. SPIE 0638, Hybrid Image Processing, (15 October 1986); https://doi.org/10.1117/12.964279
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KEYWORDS
Fractal analysis
Image resolution
Francium
Image processing
Image classification
Detection and tracking algorithms
Image segmentation
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