A comparison Study of Image Edge Segmentation Methods using Prewitt, Sobel and Laplacian of Gaussian for Medical Images
DOI:
https://doi.org/10.32792/jeps.v12i2.161Keywords:
Image segmentation, Edge detection,, Prewitt,, Sobel,, Laplacian of Gaussian, PSNR, SNRAbstract
Image processing has an important and main role in several fields. It uses to understand and discover the
image and its objects in efficiently and meaningful way. The understanding is a main step to extract
information form image. The more realization has been established from different scientists in the field
for image segmentation. The main segmentation purpose is to detect the edges information which
available inside an image clearly. Edges are the important character for image and it has produced by
summaries of the things. Mostly, Edge detection steps and its techniques have employed to evaluate and
analysis of image characteristic. Many and several kinds of techniques for detecting the edges from any
type of images. This paper has achieved the comprehensive analysis about the many edge detection
techniques like Prewitt, Sobel and Laplacian of Gaussian. The comparisons are in terms PSNR (Peak
signal to noise ratio), SNR (Signal to noise ratio) and Entropy. Finally, experimentally observed that
Laplacian of Gaussian technique is working well and recorded better results than others techniques.
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