Title: A novel fuzzy edge detection of seismic images based on bi-level maximum entropy thresholding

Authors: Sanjay Kumar Singh, Kirat Pal, M.J. Nigam

Addresses: Earthquake Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India. ' Earthquake Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India. ' Electronics and Computer Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, India

Abstract: The study of edge detection techniques in earthquake engineering is extremely important for recognition of seismic faults in the viewpoint of disaster prevention. Further, Seismic datasets are huge (several terabytes), redundant and complex. Hence, cost increases to large extent for storage and transmission against the limited memory and bandwidth. This paper presents a novel fuzzy edge detection technique of seismic images based on bi-level maximum entropy thresholding principle. Seismic edge images are obtained based on the concept of fuzzy conditional probabilities, fuzzy partition and adaptively searching the two-level optimal threshold through maximum fuzzy entropy of seismic gradient images.

Keywords: digital image processing; computer vision; edge detection; image thresholding; image segmentation; fuzzy probability; fuzzy partition; fuzzy entropy; fuzzy edge detection; fuzzy image processing; seismology; seismic image processing; earthquake engineering; disaster prevention; maximum entropy thresholding.

DOI: 10.1504/IJSISE.2010.036889

International Journal of Signal and Imaging Systems Engineering, 2010 Vol.3 No.3, pp.169 - 178

Received: 16 Nov 2009
Accepted: 14 Sep 2010
Published online: 15 Nov 2010 *

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