SEGMENTATION OF BILEVEL IMAGES USING MATHEMATICAL MORPHOLOGY
Jin-Chang Cheng, Hon-Son Don · International Journal of Pattern Recognition and Artificial Intelligence · 1992
This paper presents the results of a study on the use of morphological skeleton transformation to segment gray-scale images into bilevel images. When a bilevel image (such as printed texts and machine tools) is digitized, the result is a gray-scale image due to the point spread function of digitizer, non-uniform illumination and noise. Our method can recover the original bilevel image from the gray-scale image. The theoretical basis of the algorithm is the physical structure of the skeleton set. A connectivity property of the gray-scale skeleton transformation is used to separate and remove the background terrain. The object pixels can then be obtained by applying a global threshold. Experimental results are given.