Recognition of machine printed broken characters based on gradient patterns and its spatial relationship

Recognition of degraded characters is a challenging problem in the field of document image analysis. Two main reasons for degradation of characters are due to noise scanning and intrinsic degradation caused by font variations. The degradation of characters is mostly in the form of characters being broken at several places which hinders their recognition of OCR systems. Many OCRs have been designed which correctly identify fine printed characters without any anomalies. However, very few research works has been reported on the recognition of the degraded character recognition due to its complexity. The efficiency of the OCRs system decreases if the input image is degraded and the characters are broken at several places, which frequently occur in old documents. In this paper, a novel approach based on slope pattern and its spatial relationship is used for recognizing broken characters. The proposed method is based on the computation of slope pattern of the individual characters in eight view-directions and generating image code for each character. The algorithm has been applied on the broken characters with successful results.