S K T Hwa and Abdullah Bade and Mohd. Hanafi Ahmad Hijazi (2020) Enhanced Canny edge detection for Covid-19 and pneumonia X-Ray images. In: International Conference on Virtual and Mixed Reality Interfaces 2020, 16 - 17 November 2020, Johor, Malaysia.
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Abstract
In image processing, one of the most fundamental technique is edge detection. It is a process to detect edges from images by identifying discontinuities in brightness. In this research, we present an enhanced Canny edge detection technique. This method integrates local morphological contrast enhancement and Canny edge detection. Furthermore, the proposed edge detection technique was also applied for pneumonia and COVID-19 detection in digital x-ray images by utilising convolutional neural networks. Results show that this enhanced Canny edge detection technique is better than the traditional Canny technique. Also, we were able to produce classifiers that can classify edge x-ray images into COVID-19, normal, and pneumonia classes with high accuracy, sensitivity, and specificity.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Keyword: | Image processing , Canny edge , Covid-19 |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics |
| Department: | FACULTY > Faculty of Science and Natural Resources |
| Depositing User: | SAFRUDIN BIN DARUN - |
| Date Deposited: | 20 Oct 2022 09:37 |
| Last Modified: | 20 Oct 2022 09:37 |
| URI: | https://eprints.ums.edu.my/id/eprint/28929 |
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