Title :
Gray level thresholding in badly illuminated images
Author_Institution :
Dept. of Comput. Sci., Calgary Univ., Alta., Canada
fDate :
8/1/1991 12:00:00 AM
Abstract :
The thresholding method involves first locating objects in an image by using the intensity gradient, then noting the levels that correspond to the objects in various areas of the image, and finally using these levels as initial guesses at a threshold. This method is capable of thresholding images that have been produced in the context of variable illumination. The thresholding method, called the local intensity gradient (LIG) method, was implemented in C using a Sun4 host running UNIX. The LIG method was compared against iterative selection (IS), gray level histograms (GLHs) and two correlation based algorithms on a dozen sample images under three different illumination effects. Overall, the LIG method, while it takes significantly longer, properly thresholds a larger set of images than does any other method examined over the sample images tested
Keywords :
computerised pattern recognition; computerised picture processing; badly illuminated images; correlation based algorithms; gray level histograms; gray level thresholding; intensity gradient; iterative selection; local intensity gradient; Computer science; Correlation; Data mining; Histograms; Image analysis; Image processing; Image segmentation; Lighting; Machine intelligence; Pixel;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on