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Proceedings Paper

Deformation-Tolerant Statistical Correctors For Enhancement Of Ship Silhouette Recognition
Author(s): Mark S. Schmalz; Frank M. Caimi
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Paper Abstract

A deformation-tolerant method for classification/recognition of low resolution (FLIR regime) ship imagery is presented which employs statistical transformations and correctors based on concepts of fractal geometry. Fractal analyses, applied to specific classes of contours, present advantages of high recognition accuracy, position- and size-invariance and are suitable for microprocessor-based implementation due to low computational and storage requirements. The relationship between deformation-tolerance, superstructure geometry, and inherent transformation characteristics is presented in terms of image-plane distortions induced by out-of-plane ship rotation. Comparison algorithms using feature-space correctors derived from the fractal dimension are discussed in terms of classification and recognition success rates and computational load.

Paper Details

Date Published: 16 September 1987
PDF: 12 pages
Proc. SPIE 0781, Infrared Image Processing and Enhancement, (16 September 1987); doi: 10.1117/12.940546
Show Author Affiliations
Mark S. Schmalz, Harbor Branch Oceanographic Institution, Inc. (United States)
Frank M. Caimi, Harbor Branch Oceanographic Institution, Inc. (United States)


Published in SPIE Proceedings Vol. 0781:
Infrared Image Processing and Enhancement
Marshall R. Weathersby, Editor(s)

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