Smart Edge Detection Technique in X-ray Images for Improving PSNR using Prewitt Edge Detection Algorithm with Gaussian Filter in Comparison with Laplacian Algorithm

Abstract

Aim: This study aims to propose smart edge detection techniques in x-ray images for improving PSNR using the Prewitt edge detection algorithm and comparing it with the laplacian algorithm. Materials and methods: For the design of edge detection technique to improve PSNR Prewitt edge detection algorithm is used along with a gaussian filter and it is compared with the laplacian algorithm. Prewitt edge detection algorithm and laplacian algorithm are the two groups considered in this study. For each group, the sample size is 20 and the total sample size is 40. Sample size calculation was done using clinicalc. com by keeping g-power at 80%, confidence interval at 95%, and the threshold at 0.05%. Result: When comparing the two algorithms, it is clear that the Prewitt edge detection algorithm has a higher mean PSNR value of 39.19 db than the laplacian algorithm of 37.56 db. It is observed that the Prewitt edge detection algorithm is statistically significant p<0.05 than the laplacian algorithm by performing an independent sample t-test. Conclusion: Prewitt edge detection has insignificantly greater PSNR when compared to the Laplacian algorithm.