Nowadays the research on OCR system focuses on corrupted and damaged characters from printed and handwritten documents. Many researches have been done on touching charac-ters but only few on broken characters. This paper presents a new method to reconstruct printed characters extracted as many connected components. Our approach is based on the pat-tern similarity between broken characters and perfect ones from the same printed document. In the first step, we use a multi-segmentation algorithm to extract all possible connected compo-nents from a document image digitized in grayscale, and then we order them by their size. The correctly segmented characters are supposed to be bigger than the parts of miss-recognized ones. We compute a similarity measure between all connected components, in decreasing order of their size. Then we localize the broken characters by using the bounding box of the correct pattern which have the best match.