  The existing traditional edge detection algorithms process a single pixel on
an image at a time, thereby calculating a value which shows the edge magnitude
of the pixel and the edge orientation. Most of these existing algorithms
convert the coloured images into gray scale before detection of edges. However,
this process leads to inaccurate precision of recognized edges, thus producing
false and broken edges in the image. This paper presents a profile modelling
scheme for collection of pixels based on the step and ramp edges, with a view
to reducing the false and broken edges present in the image. The collection of
pixel scheme generated is used with the Vector Order Statistics to reduce the
imprecision of recognized edges when converting from coloured to gray scale
images. The Pratt Figure of Merit (PFOM) is used as a quantitative comparison
between the existing traditional edge detection algorithm and the developed
algorithm as a means of validation. The PFOM value obtained for the developed
algorithm is 0.8480, which showed an improvement over the existing traditional
edge detection algorithms.
