Improving text recognition by distinguishing scene and overlay text

Bernhard Quehl; Haojin Yang; Harald Sack

doi:10.1117/12.2181370

14 February 2015 Improving text recognition by distinguishing scene and overlay text

Bernhard Quehl, Haojin Yang, Harald Sack

Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 944509 (2015) https://doi.org/10.1117/12.2181370
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

Video texts are closely related to the content of a video. They provide a valuable source for indexing and interpretation of video data. Text detection and recognition task in images or videos typically distinguished between overlay and scene text. Overlay text is artificially superimposed on the image at the time of editing and scene text is text captured by the recording system. Typically, OCR systems are specialized on one kind of text type. However, in video images both types of text can be found. In this paper, we propose a method to automatically distinguish between overlay and scene text to dynamically control and optimize post processing steps following text detection. Based on a feature combination a Support Vector Machine (SVM) is trained to classify scene and overlay text. We show how this distinction in overlay and scene text improves the word recognition rate. Accuracy of the proposed methods has been evaluated by using publicly available test data sets.

Citation Download Citation

Bernhard Quehl, Haojin Yang, and Harald Sack "Improving text recognition by distinguishing scene and overlay text", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944509 (14 February 2015); https://doi.org/10.1117/12.2181370

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