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Statistical-based approach to word segmentation

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3 Author(s)
Wang, Y. ; Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA ; Phillips, I.T. ; Haralick, R.

This paper presents a text word extraction algorithm that takes a set of bounding boxes of glyphs and their associated text lines of a given document and partitions the glyphs into a set of text words, using only the geometric information of the input glyphs. The algorithm is probability based. An iterative, relaxation-like method is used to find the partitioning solution that maximizes the joint probability. To evaluate the performance of our test word extraction algorithm, we used a 3-fold validation method and developed a quantitative performance measure. The algorithm was evaluated on the UW-III database of some 1600 scanned document image pages. An area-overlap measure was used to find the correspondence between the detected entities and the ground-truth. For a total of 827, 433 ground truth words, the algorithm identified and segmented 800, 149 words correctly, an accuracy of 97.43%

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Pattern Recognition, 2000. Proceedings. 15th International Conference on  (Volume:4 )

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