Object detection using a novel 2-D adaptive sampling strategy

This paper describes a novel algorithm especially devoted to detect "interesting" objects defined as a set of close measured values that spring out from a uniform or textured background. In particular such an algorithm has been developed with the purpose to define a movement strategy for a...

Full description

Saved in:
Bibliographic Details
Published in2000 10th Mediterranean Electrotechnical Conference. Information Technology and Electrotechnology for the Mediterranean Countries. Proceedings. MeleCon 2000 (Cat. No.00CH37099) Vol. 2; pp. 627 - 630 vol.2
Main Authors Mulassano, P., Avagina, D., Lo Presti, L.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2000
Subjects
Electromagnetic fields
Geophysical measurements
Geophysics
Image sampling
Object detection
Performance evaluation
Phase detection
Sampling methods
Shape
Springs
Online AccessGet full text

Cover

More Information
Summary:This paper describes a novel algorithm especially devoted to detect "interesting" objects defined as a set of close measured values that spring out from a uniform or textured background. In particular such an algorithm has been developed with the purpose to define a movement strategy for a remotely piloted rover useful in applied geophysics. The method could be represented by a Viper that moves with a random trial over the image with the purpose to detect the presence of an object emerging from the background, and to adapt the sampling interval to the shape of the detected object. Simulations on real geophysics images show good results with reduced algorithm complexity.
ISBN:078036290X
9780780362901
DOI:10.1109/MELCON.2000.880012