TITLE:
Edge Detection with a Preprocessing Approach
AUTHORS:
Mohamed Abo-Zahhad, Reda Ragab Gharieb, Sabah M. Ahmed, Ahmed Abd El-Baset Donkol
KEYWORDS:
Discrete Wavelet Transform, Image Edge Detection, Robert, Prewitt, Sobel, Canny Techniques
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.5 No.4,
October
15,
2014
ABSTRACT: Edge detection is the
process of determining where boundaries of objects fall within an image. So
far, several standard operators-based methods have been widely used for edge
detection. However, due to inherent quality of images, these methods prove
ineffective if they are applied without any preprocessing. In this paper, an
image preprocessing approach has been adopted in order to get certain
parameters that are useful to perform better edge detection with the standard
operators-based edge detection methods. The proposed preprocessing approach
involves computation of the histogram, finding out the total number of peaks
and suppressing irrelevant peaks. From the intensity values corresponding to
relevant peaks, threshold values are obtained. From these threshold values,
optimal multilevel thresholds are calculated using the Otsu method, then
multilevel image segmentation is carried out. Finally, a standard edge
detection method can be applied to the resultant segmented image. Simulation
results are presented to show that our preprocessed approach when used with a
standard edge detection method enhances its performance. It has been also shown
that applying wavelet edge detection method to the segmented images, generated
through our preprocessing approach, yields the superior performance among other
standard edge detection methods.