Edge detection based on augmented lagrangian method for lowquality medical images

Authors

DOI:

10.46223/HCMCOUJS.tech.en.8.1.910.2018

Keywords:

augmented lagrangian method; canny; edge detection

Abstract

Medical images are useful for the treatment process. They contain a lot of information on displaying abnormalities in your body. The contour of medical images is a matter of interest. In there, edge detection is a process prepared for boundaries. Therefore, the edge detection of medical images is very important. Other previous methods must sacrifice time for the accurate results. It is because the medical images in the real world have many impurities. In this paper, I propose a method of detecting edges in medical images which have impurities by using augmented lagrangian method to improve the Canny algorithm. My algorithm improves the ability to detect edges faster. Compared with other recent methods, the proposed method is more efficient.

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References

Bhatt, A. D., & Warkhedkar, R. V. (2008). Reverse engineering of human body: A B-Spline based heterogeneous modeling approach. Computer-Aided Design and Applications, 5(1/4), 194-208.

Bhatt, A. D., & Warkhedkar, R. V. (2009). Material-solid modeling of human body: A heterogeneous B-Spline based approach. Computer-Aided Design, 41(8), 586-597.

Brigger, P., & Unser, M. (1998). Multi-scale B-spline snakes for general contour detection. Wavelet Applications in Signal and Image Processing VI, SPIE, 3458, 92-102.

Canny, J. (1986). A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, PAMI, 8(6), 679-698.

Deriche, R. (1987). Using Canny's criteria to derive a recursively implemented optimal edge detector. International Journal of Computer Vision, 1, 167-187.

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Received: 17-08-2020
Accepted: 17-08-2020
Published: 17-08-2018

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How to Cite

Tuyet, V. T. H. (2018). Edge detection based on augmented lagrangian method for lowquality medical images. HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, 8(1), 106–115. https://doi.org/10.46223/HCMCOUJS.tech.en.8.1.910.2018