|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Title:||Multi-oriented text extraction from information graphics|
|Citation:||Böschen F & Scherp A (2015) Multi-oriented text extraction from information graphics. In: Proceedings of the 2015 ACM Symposium on Document Engineering (DocEng '15). 2015 ACM Symposium on Document Engineering, Lausanne, Switzerland, 08.09.2015-11.09.2015. New York: ACM, pp. 35-38. https://doi.org/10.1145/2682571.2797092|
|Conference Name:||2015 ACM Symposium on Document Engineering|
|Conference Dates:||2015-09-08 - 2015-09-11|
|Conference Location:||Lausanne, Switzerland|
|Abstract:||Existing research on analyzing information graphics assume to have a perfect text detection and extraction available. However, text extraction from information graphics is far from solved. To fill this gap, we propose a novel processing pipeline for multi-oriented text extraction from infographics. The pipeline applies a combination of data mining and computer vision techniques to identify text elements, cluster them into text lines, compute their orientation, and uses a state-of-the-art open source OCR engine to perform the text recognition. We evaluate our method on 121 infographics extracted from an open access corpus of scientific publications. The results show that our approach is effective and significantly outperforms a state-of-the-art baseline.|
|Status:||VoR - Version of Record|
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|Böschen-Scherp 2015.pdf||Fulltext - Published Version||469.59 kB||Adobe PDF||Under Permanent Embargo Request a copy|
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