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A New Algorithm for Detecting Text Line in Handwritten Documents

Yi Li, Yefeng Zheng, David Doermann and Stefan Jaeger


ABSTRACT

Curvilinear text line detection and segmentation in handwritten documents is a significant challenge for handwriting recognition. Given no prior knowledge of script, we model text line detection as an image segmentation problem by enhancing text line structure using a Gaussian window, and adopting the level set method to evolve text line boundaries. Experiments show that the proposed method achieves high accuracy for detecting text lines in both handwritten and machine printed documents with many scripts.

Reference: 10th International Workshop on Frontiers in Handwriting Recognition, pages 35-40, 2006. (BibTex)

Manuscript: (PDF)




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