DESCRIPTION =========== The program performs smoothing of curves. Appropriate levels of smoothing are determined for dynamically determined sections of the curves. Details are described in the paper "Non-parametric multiscale curve smoothing" by Paul L. Rosin in International J. of Pattern Recognition and Artificial Intelligence, vol. 8, no. 6, pp. 1381-1406, 1994. DATA FORMAT =========== Input curves are stored in a simple ASCII format. Each file starts with "pixel". Each connected chain of edge pixels is preceded by "list: ID", where ID is (usually but not necessarily) a unique integer for each curve, and is terminated by "-1 0", except for the last list which is terminated by "-1 -1". Between the list header and terminator the integer co-ordinates of each pixel are given. Output can either be: (1) "pixel_float" which is identical to "pixel" except that the co-ordinates are stored as floating point values, (2) "pixel_curvature" which includes the curvature and a singular point label with each co-ordinate and includes on the line following the "list: ID" statement a "sigma: FLOAT" statement specifying the amount of smoothing that was performed, or (3) Postscript EXAMPLES ======== A sample data file "lena.pix" is provided. To perform Gaussian smoothing using the points of maximum deviation as breakpoints and outputing a Postscript file do: best_smooth -i lena.pix -o f1 -b 1 To perform polynomial fitting using the midpoint as breakpoint, and outputing in "pixel" format do: best_smooth -i lena.pix -o f2 -s 1 -f --------------------------------------------------------------- Dr. Paul Rosin Department of Computer Science & Information Systems Brunel University Kingston Lane email: Paul.Rosin@brunel.ac.uk Uxbridge tel: +44-1895-274000 ext. 3632 Middlesex UB8 3PH fax: +44-1895-251686 ---------------------------------------------------------------