Synthesis and analysis of afficiency of algorithm for objects edges detection by maximum likelihood method

Edge detection algorithm, which takes into account difference in fractal dimensions of object and background, is synthesized by maximum likelihood method. Adaptive algorithm of edge detection is proposed under a priori uncertainty of fractal dimensions values. This algorithm contains correlation dim...

Full description

Saved in:
Bibliographic Details
Published inMediterranean Conference on Embedded Computing (New Jersey. Online) pp. 223 - 226
Main Authors Alexandr, Parshin, Yury, Parshin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2013
Subjects
a priori uncertainty
Adaptation models
Algorithm design and analysis
Chaos
fractal dimension
Image edge detection
integration of algorithms
maximum likelihood method
object edge detection
Uncertainty
Online AccessGet full text
ISSN2377-5475
DOI10.1109/MECO.2013.6601363

Cover

More Information
Summary:Edge detection algorithm, which takes into account difference in fractal dimensions of object and background, is synthesized by maximum likelihood method. Adaptive algorithm of edge detection is proposed under a priori uncertainty of fractal dimensions values. This algorithm contains correlation dimension estimates which have been evaluated in terms of observable data. Efficiency comparison of different versions of image data reading for different objects edge position regarding reading direction is made. Algorithm analysis is carried out under complete and incomplete a priori information.
ISSN:2377-5475
DOI:10.1109/MECO.2013.6601363