Edge Detection Using Sparse Coding Method
Yan Ping Yang, Kang Gewen, Hong Li · 2009
Sparse coding is a method for finding a neural network representation of multidimensional data in which each of the components of the representation is rarely ignorantly active at the same time. The representation is closely related to Independent Component Analysis (ICA). In this paper, we introduced the basic principle of ICA and have investigated the capabilities of ICA in the field of image edge detection. We have also performed practical implementation of ICA and applied to edge detection through the basis as the sample template. We have seen that ICA outperforms basic edge detection methods such as Canny, Robert, Sobel and Prewitt.