Fractal Image Models And Object Detection

Michael C. Stein

doi:10.1117/12.976518

13 October 1987 Fractal Image Models And Object Detection

Michael C. Stein

Proceedings Volume 0845, Visual Communications and Image Processing II; (1987) https://doi.org/10.1117/12.976518
Event: Cambridge Symposium on Optics in Medicine and Visual Image Processing, 1987, San Diego, CA, United States

Abstract

This paper discusses a new technique for object detection that uses fractals to model the natural background in a visible image. Our technique is based on the fact that fractal-based models have been found to be good models for natural objects as well as images of natural objects. On the other hand, man-made objects are decidedly not self-similar and therefore fractal-based models are not good models for man-made objects and their images. The technique adaptively fits a fractal-based model and a 2-D autoregressive model over the image and the fractal dimension and model-fit errors are used to identify regions of anomalous dimension and high error. Thus the technique uses a dual approach to object detection by modeling and deemphasizing the natural background instead of explicitly modeling and identifying the man-made object. Results are shown for a real image.

Citation Download Citation

Michael C. Stein "Fractal Image Models And Object Detection", Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); https://doi.org/10.1117/12.976518

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