Context-directed segmentation algorithm for handwritten numeral strings
Image and Vision Computing
A Survey of Methods and Strategies in Character Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segment confidence-based binary segmentation (SCBS) for cursive handwritten words
Expert Systems with Applications: An International Journal
Proceedings of the 2012 ACM symposium on Document engineering
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Segmentation of connected handwritten Chinese characters is a very difficult task in document image analysis. In this paper, a novel algorithm based on stroke analysis and background thinning is proposed to segment connected handwritten Chinese characters. The feature points, viz. end points, fork points and comer points are detected in the thinned image. The segments between feature points are considered as substrokes and are extracted. Lengths of substrokes and the topological relations between them are employed to locate connected point. A new method based on background thinning is developed to decide a proper segmentation path. The experimental results show that satisfactory performance is achieved by the presented method for segmentation of connected handwritten Chinese characters.