Existing skeletonization methods operate directly on the binary image ignoring the gray-level information. In this paper we propose a new method for the skeletonization of handwritten characters that uses gray-level information and capitalizes on their elongated pattern properties. The method controls the development of the skeleton while iteratively binarizing the gray-level image. Two types of iterations are performed: the iterative skeletonization and deletion of boundary pixels, which is nested within the iterative binarization of the gray-level image. Detailed analysis of the skeletonization process is presented to show its superior performance related to the prevention of "flooding water" and end point shrinkage and to noise immunity.