New scheme for off-line handwritten connected digit recognition

In this study, we introduce a new scheme for off-line handwritten connected digit string recognition problem, which uses a sequence of segmentation and recognition algorithms. The proposed system assumes no constraint in writing style, size or variations. First, a segmentation method, which combines the gray scale and binary information, is proposed to find the nonlinear character segmentation paths. Each segment is then, recognized by a Hidden Markov Model (HMM). Finally, in order to confirm the segmentation paths and recognition results, a recognition based segmentation method is presented. The proposed scheme is tested on 4000 handwritten connected digit, collected from 16 different persons. The experiments yield 97.2% recognition rate.