Examination paper text detection based on character discriminator

Linteng Wang; Xiaoguang Li

doi:10.1117/12.2539618

14 August 2019 Examination paper text detection based on character discriminator

Linteng Wang, Xiaoguang Li

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791Z (2019) https://doi.org/10.1117/12.2539618
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

Examination paper text detection poses a challenging task of detecting text lines from examination paper with different sizes, low resolution, handwritten character and print character mixed, etc. In this paper, we propose a simple yet effective text detection method base on character discriminator (TDCD) to tackle the problem of examination paper text detection. We aim at detecting text lines of examination paper refer to high-quality character rectangles using the text line construction approach. To obtain the high-quality character rectangles, we firstly leverage canny filter and bounding rectangle tool for producing the bounding rectangles of examination paper connected regions. Then, the candidate rectangles generated by the merging of the bounding rectangles base on IOU. We finally propose a character discriminator (CD) to guide different candidate rectangles of a character to merge. Furthermore, we collect and annotate an examination paper image dataset EPDB-100. We conduct extensive experiments on EPDB-100. In particular, our TDCD achieves the F-measure score of 63.5%.

Citation Download Citation

Linteng Wang and Xiaoguang Li "Examination paper text detection based on character discriminator", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791Z (14 August 2019); https://doi.org/10.1117/12.2539618

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KEYWORDS

Detection and tracking algorithms

Image processing

Image filtering

Convolution

Image quality

Image resolution

Image segmentation

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