cnn

Neural networks for image processing: new edge detection algorithm

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.
1. Introduction