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An Optical Character Recognition (OCR) system with high recognition rate is challenging to develop. One of the major contributors to OCR errors is smeared characters. Several factors lead to the smearing of characters such as bad scanning and a poor binarization technique. Typical approaches to character segmentation falls into three major categories: image-based, recognition-based and holistic-based. Among these approaches, the segmentation path can be linear or non-linear. Our paper proposes a non-linear approach to segment the characters on grayscale document images. Our method first determines whether characters are smeared together using general character features. The correct segmentation path is found using a Routing based Reach Algorithm. The replacement paths in the Algorithm make Robust and speedup the Reach Algorithm. This method corrects most of errors produced by segmentation process. We achieved a segmentation accuracy of 97% with less computation time over a set of about 4,000 smeared characters. This approach is useful in real-time applications for robust OCR with smeared character detection and provides accurate character recognition with less computation time under various recognition scenarios.