A novel fuzzy edge detection of seismic images based on bi-level maximum entropy thresholding. (16th November 2010)

• Record Type: Journal Article
• Authors: Singh, Sanjay Kumar; Pal, Kirat; Nigam, M.J.
• Is Part Of: International journal of signal and imaging systems engineering. Volume 3:Number 3(2010)
• Page Start: 169
• Page End: 178
• Publication Date: 2010-11-16
• Subjects: 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; Signal processing -- Periodicals; Imaging systems -- Periodicals; Information theory -- Periodicals; 621.3822
• Languages: English
• ISSNs: 1748-0698

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.