comparison of edge detection algorithm

we have to compare the algorithm and then got the output in matlab code.

Neural networks can be very useful for image
processing applications. This paper exploits the Cellular
Neural Network (CNN) paradigm to develop a new edge
detection algorithm. The approach makes use of rigorous
model of the image contours, and takes into account some
electrical restrictions of existing CNN-based hardware
implementations. Four benchmark video sequences are
analyzed, that is, Car-phone, Miss America, Stefan, and
Foreman. The analysis shows that the proposed algorithm
yields accurate results, better than the ones achievable by
other CNN-based methods. Finally, comparisons with
standard edge detection techniques (i.e., LoG edge
detector and Canny algorithm) further confirm the
capability of the developed approach.