Discrimination and Thresholding

Abstract

There have been several references in the preceding chapters to the use of brightness discrimination to select pixels belonging to features of interest. This is a widely used method of converting a grey scale image to a binary (black and white) one, illustrated in Figure 5-1. Discrimination with threshold values is much more efficient than any edge following or region growing method (as discussed in the previous chapter) because it works on the entire image at once. Hence the time required is fixed, regardless of the complexity of the image, and very short. Also, the resulting binary image is a pixel-based representation of features of interest, and is easier for most measurement operations than the boundary representation that results from the location and identification of edges.