An adept edge detection algorithm for human knee osteoarthritis images

Syed Zahurul, Syed Zahidul, Razali Jidin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Digital image processing comprises varieties of applications, where some of these used in medical image processing include convolution, edge detection as well as contrast enhancement. Efficient edge detection depends on choosing the threshold; the choice of threshold directly determines the results of edge detection. In this paper, Sobel edge detection operator and its enhanced algorithm are first discussed in terms of optimal thresholding in C language under Linux platform. It is implemented a competent execution time for this new enhanced algorithm to detect edges for human knee osteoarthritis images in different critical situations. The proposed method is able to exhibit discernible view of salient features of most osteoarthritis images with approximately 50% better execution time compare to classical Sobel method. Also, it is shown that the algorithm is very effective in case of noisy and blurs images.

Original languageEnglish
Title of host publication2010 International Conference on Signal Acquisition and Processing, ICSAP 2010
Pages375-379
Number of pages5
DOIs
Publication statusPublished - 18 May 2010
Event2010 International Conference on Signal Acquisition and Processing, ICSAP 2010 - Bangalore, India
Duration: 09 Feb 201010 Feb 2010

Publication series

Name2010 International Conference on Signal Acquisition and Processing, ICSAP 2010

Other

Other2010 International Conference on Signal Acquisition and Processing, ICSAP 2010
CountryIndia
CityBangalore
Period09/02/1010/02/10

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All Science Journal Classification (ASJC) codes

  • Signal Processing

Cite this

Zahurul, S., Zahidul, S., & Jidin, R. (2010). An adept edge detection algorithm for human knee osteoarthritis images. In 2010 International Conference on Signal Acquisition and Processing, ICSAP 2010 (pp. 375-379). [5432947] (2010 International Conference on Signal Acquisition and Processing, ICSAP 2010). https://doi.org/10.1109/ICSAP.2010.53