Hidden loop recovery for handwriting recognition

One significant challenge in the recognition of off-line handwriting is in the interpretation of loop structures. Although this information is readily available in online representation, close proximity of strokes often merges their centers making them difficult to identify. In this paper a novel approach to the recovery of hidden loops in off-line scanned document images is presented. The proposed algorithm seeks blobs that resemble truncated ellipses. We use a sophisticated form analysis method based on mutual distance measurements between the two sides of a symmetric shape. The experimental results are compared with the ground truth of the online representations of each off-line word image. More than 86% percent of the meaningful loops are handled correctly.