There is a long history of perturbed implementations of Abel differential equations in dynamics, linear systems with stochasticity, modeling approaches, and linear algebra. Numerous research has been undertaken, the bulk of which have focused on Abel differential equation techniques and the use of the Abel differential equation using the variation iteration method. Edges define boundaries and are hence of primary relevance in image processing. Edge detection removes unnecessary data, noise, and frequencies from a picture while maintaining crucial structural aspects. To extract edges based on canny, the suggested technique employs fractional Abel differential equation (FADE) logic. In this case, a picture is used with the windowing technique and is submitted to a series of Abel differential equations. The purpose of this research is to assess the performance of a FADE system in edge detection. The results produced by the linear canny operator are compared to those obtained with pictures with substantial contrast variation. This experimental investigation will provide a faster procedure and a better output image than the current methods. The main goal of the proposed technique is to use the edge points and the information they collect for edge identification, resulting in faster and more accurate results. For all of the experimental experiments, MATLAB software was employed.
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