Edges are intensity change, which occur on the boundary between two regions in an image. Edges can be used as feature descriptors of an object. Hence, edge detection plays an important role in computer vision applications. This paper presents the application of sparse banded filter matrices in edge detection. The filter design is formulated in terms of banded matrices. The sparsity property of the designed filter leads to efficient computation. In our proposed method, we applied sparse banded high-pass filter row-wise and column-wise to extract the vertical and the horizontal edges of the image respectively. The proposed technique is experimented on standard images and the results are compared with the state-of-the-art methods. The visual comparison of the experimental results shows that the proposed approach for edge extraction based on sparse banded filter matrices produces result comparable to the existing methods. The advantage of the proposed approach is that the continuous edges are attained without any parameter tuning.
Sowmya V., Neethu Mohan, and Soman, K. P., “Edge Detection Using Sparse Banded Filter Matrices”, Second International Symposium on Computer Vision and the Internet (VisionNet’15). Elsevier Procedia Computer Science Journal, SCMS School of Engineering, Aluva, Kochi , pp. 10–17, 2015.