CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1983 vol.5 Issue No.03 - March
Issue No.03 - March (1983 vol.5)
Raul Machuca , White Sands Missile Range, U.S. Army, White Sands, NM 88002.
Keith Phillips , Department of Mathematics, New Mexico State University, Las Cruces, NM 88003; White Sands Missile Range, U.S. Army, White Sands, NM 88002.
We use rotational and curvature properties of vector fields to identify critical features of an image. Using vector analysis and dif-ferential geometry, we establish the properties needed, and then use these properties in three ways. First, our results make it theoretically possible to identify extremal edges of an intensity function f(x, y) of two variables by considering the gradient vector field V = ¿f. There is also enough information in ¿f to find regions of high curvature (i.e., high curvature of the level paths of f). For color images, we use the vector field V = (I, Q). In application, the image is partitioned into a grid of squares. On the boundary of each square, V/|V| is sampled, and these unit vectors are used as the tangents of a curve ¿. The rotation number (or topological degree) ¿(¿) and the average curvature f|¿¿| are computed for each square. Analysis of these numbers yields infor-mation on edges and curvature. Experimental results from both simu-lated and real data are described.
Raul Machuca, Keith Phillips, "Applications of Vector Fields to Image Processing", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.5, no. 3, pp. 316-329, March 1983, doi:10.1109/TPAMI.1983.4767393