Combined edge detection using wavelet transform and signal registration

Dušan Heric (Author), Damjan Zazula (Author)

Abstract

This paper presents a novel edge detection algorithm, using Haar wavelet transform and signal registration. The proposed algorithm has two stages: (a) adaptive edge detection with the maximum entropy thresholding technique on time-scale plane and (b) edge linkage into a con tour line with signal registration in order to c1ose edge discontinuities and calculate a confidence index for contour linkages. This index measures the level of confidence in the linkage of two adjacent points in the con tour structure. Experimenting with synthetic images, we found out the lower level of confidence can be set to approximately e-2. The method was tested on 200 synthetic images at different signal-to-noise ratios (SNRs) and II clinical images. We assessed its reliability, accuracy and robustness using the mean absolute distance (MAD) metric and our confidence index. The results for MAD on synthetic images yield the mean of 0.7 points and standard deviation (std) of 0.14, while the mean confidence level is 0.48 with std of 0.19 (the values are averaged over SNRs from 3 to 50 dB each in 20 Monte-Carlo runs). Our assessment on clinical images, where the references were expert's annotations, give MAD equal1.36:1:: 0.36 (mean :1:: std) and confidence level equal 0.67 :1:: 0.25 (mean :1:: std).

Keywords

edge model;edge detection;wavelet transform;signal registration;

Data

Language:	English
Year of publishing:	2006
Typology:	1.01 - Original Scientific Article
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
UDC:	004.92
COBISS:	10862614
ISSN:	0262-8856
Views:	1723
Downloads:	89
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
URN:	URN:SI:UM:
Pages:	str. 652-662
Volume:	ǂVol. ǂ25
Issue:	ǂno. ǂ5
Chronology:	2007
DOI:	10.1016/j.imavis.2006.05.008
ID:	8717132