Method and system for measuring surface roughness using fractal dimension values

A method of measuring surface roughness, comprising the steps of:

• forming a V.times.W video image of a surface area;
• partitioning said V.times.W video image into a set of regions that cover said V.times.W video image, each of said regions being of equal size v.times.w with v.ltoreq.V and w.ltoreq.W;
• calculating a fractal dimension value for each of said regions;
• averaging said fractal dimension values for said regions to form an average fractal dimension value associated with said size v.times.w;
• and
• repeating said steps of partitioning, calculating and averaging for i additional sets of regions, each region from an i-th additional set being of an equal and unique size v.sub.i .times.w.sub.i with v.sub.i .ltoreq.V and w.sub.i .ltoreq.W to form i additional average fractal dimension values, wherein said average fractal dimension value and said i additional average fractal dimension values plotted as a function of said size v.times.w and said sizes v.sub.i .times.w.sub.i define a best-fit straight line satisfying the equation y=mx+b where m is a slope of said best-fit straight line and b is a y-intercept of said best-fit straight line, wherein a combination of said slope and said y-intercept is indicative of surface roughness of said surface area.

A method of measuring surface roughness, comprising the steps of:

• forming a video image of a surface area, said video image being of size V.times.W;
• calculating a fractal dimension value for said video image;
• partitioning said video image into a set of regions that cover said video image, each of said regions being of equal size v.times.w with v<V and w<W;
• calculating a fractal dimension value for each of said regions;
• averaging said fractal dimension values for said regions to form an average fractal dimension value associated with said size v.times.w;
• and
• repeating said steps of partitioning, calculating and averaging for i additional sets of regions, each region from an i-th additional set being of an equal and unique size v.sub.i .times.w.sub.i with v.sub.i <V and w.sub.i <W to form i additional average fractal dimension values, wherein a plot of said fractal dimension value for said video image, said average fractal dimension value and said i additional average fractal dimension values as a function of a sequential ordering of said size V.times.W, said size v.times.w and said sizes v.sub.i .times.w.sub.i define a best-fit straight line satisfying the equation y=mx+b where m is a slope of said best-fit straight line and b is a y-intercept of said best-fit straight line, wherein a combination of said slope and said y-intercept is indicative of surface roughness of said surface area.