Text field extraction from camera-captured express images

Yalin Yin; Dahan Wang

doi:10.1117/12.2557470

3 January 2020 Text field extraction from camera-captured express images

Yalin Yin, Dahan Wang

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 1137324 (2020) https://doi.org/10.1117/12.2557470
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

With the development of domestic express business in China, there is a potential and huge need for automatic information extraction from express mail images, which however is challenging due to the skewness/folds of the captured express mail images. This paper presents a robust approach to text extraction from camera captured express mail images. Firstly, the proposed approach use a deep direct regression neural network to predict both the express bill region and type; then the form frame lines and corners are detected, with which the Coherent Point Drift (CPD) based point matching is adopted to obtain the mapping between the template and the input image. Finally, based on the mapping, accurate writing fields can be extracted. The Experiments on realistic express mail images demonstrate the effectiveness of the proposed approach.

Citation Download Citation

Yalin Yin and Dahan Wang "Text field extraction from camera-captured express images", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137324 (3 January 2020); https://doi.org/10.1117/12.2557470

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