Evaluation of binarization methods for utility map images

This paper presents an evaluation of locally adaptive binarization methods for gray scale images with low contrast, variable background intensity and noise. Such low quality occurs frequently in utility maps and excludes the use of global binarization methods. Only robust locally adaptive binarization methods with no need for on-line tuning of the parameters were considered since the gray scale images of utility maps often consist of a billion (10⁹) pixels or more. Eight locally adaptive binarization methods were tested on five different images. The postprocessing step (PS) of Yanowitz and Bruckstein´s (1989) method improved all the other best binarization methods. Niblack´s (1986) method with PS gave the best performance. Eikvil, Taxt and Moen´s (1991) method with PS, and Yanowitz and Bruckstein´s method did almost as well. Comparison was also made on the CPU requirement