Segmentation of handwritten connected numeral string using background and foreground analysis

An approach to segmentation of handwritten connected numeral strings is proposed. Most algorithms for segmenting connected digits mainly focus on the analysis of foreground pixels. Some others concentrated on the analysis of background pixels only. We use background and foreground analysis to segment handwritten connected numeral strings. Thinning of both foreground and background pixels are first processed on the image of the numeral stroke and the feature points on foreground and background skeletons are extracted separately. Several possible segmentation paths are constructed and useless strokes are removed. Then, the parameters of geometric properties of each possible segmentation path are determined and these parameters are analyzed by mixture Gaussian probability functions to find the best segmentation path. For preliminary experimentation, we collected 150 images of handwritten connected numeral strings for test and 134 are correctly segmented (correct rate is 96.4%). 5 are in error (error rate is 3.6%) and 11 are rejected (rejected rate is 7.3%)