This paper presents an efficient method of reconstructing and recognizing broken handwritten digits. Constrained dilation algorithms are used to bridge small gaps and smooth some spurious points. The contours of broken handwritten digits are smoothed and linearized, and a set of structural points of digits are detected along the outer contours of digits. These structural points are used to describe the morphological structure of broken digits. The broken digits are skeletonized with an improved thinning algorithm. Spurious segments introduced during the extraction of digit fields are detected and deleted based on the structure analysis of digit fields, segment recognition, segment extension, skeleton structure and geometrical features. The broken points of the digits are preselected based on the minimum distance between the \end" points of skeletons of two neighboring regions. The correction rules of the preselected broken points are also based on the structure analysis and comparison of broken digits. Experimental results showing the effectiveness of the method are given.