PERFORMANCE ANALYSIS OF BONE IMAGES USING VARIOUS EDGE DETECTION ALGORITHMS AND DENOISING FILTERS

Abstract

Image preprocessing and image segmentation are two important and broad research areas. Image denoising is one of the research fields in the research area of image preprocessing which is used to remove noise from the images. This paper proposed a method to identify the best filter and best edge detection algorithm for digital x-ray bone images. Comparisons of various filters such as Mean, Median, Gaussian and Weiner over different types of noises such as Salt and Pepper noise, Gaussian noise, Poisson noise and Speckle noise are analyzed by measuring performance parameters such as Mean Square Error (MSE), Normalised Correlation Coefficient (NCC), Peak Signal to Noise Ratio (PSNR), Normalized Absolute Error (NAE), Average Difference (AD) and Structural Content (SC). Comparison of different types of edge detection algorithms is analyzed by measuring the speed of edge detection and manual analysis. The benchmark experimental results show that best filter and the best edge detection algorithm for digital x-ray bone images.