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Issue No.08 - August (1991 vol.13)
pp: 813-819
<p>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.</p>
gray level thresholding; badly illuminated images; intensity gradient; local intensity gradient; iterative selection; gray level histograms; correlation based algorithms; computerised pattern recognition; computerised picture processing
J.R. Parker, "Gray Level Thresholding in Badly Illuminated Images", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.13, no. 8, pp. 813-819, August 1991, doi:10.1109/34.85672
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