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Scene-Text-Detection Method Robust Against Orientation and Discontiguous Components of Characters

Authors: Rei Endo; Yoshihiko Kawai; Hideki Sumiyoshi; Masanori Sano;

Scene-Text-Detection Method Robust Against Orientation and Discontiguous Components of Characters

Abstract

Scene-text detection in natural-scene images is an important technique because scene texts contain location information such as names of places and buildings, but many difficulties still remain regarding practical use. In this paper, we tackle two problems of scene-text detection. The first is the discontiguous component problem in specific languages that contain characters consisting of discontiguous components. The second is the multi-orientation problem in all languages. To solve these two problems, we propose a connected-component-based scene-text-detection method. Our proposed method involves our novel neighbor-character search method using a synthesizable descriptor for the discontiguous-component problems and our novel region descriptor called the rotated bounding box descriptors (RBBs) for rotated characters. We also evaluated our proposed scene-text-detection method by using the well-known MSRA-TD500 dataset that includes rotated characters with discontiguous components.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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