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Merge branch 'master' into GSOC_text_detect_DNN_backend

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Suman Ghosh
2017-08-28 19:56:10 +02:00
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parent c697e41b8d e7547d6140
commit 731637e0bb
55 changed files with 737 additions and 683 deletions
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6
modules/text/include/opencv2/text.hpp
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@@ -55,7 +55,7 @@ Class-specific Extremal Regions for Scene Text Detection
--------------------------------------------------------
The scene text detection algorithm described below has been initially proposed by Lukás Neumann &
Jiri Matas [Neumann12]. The main idea behind Class-specific Extremal Regions is similar to the MSER
Jiri Matas @cite Neumann11. The main idea behind Class-specific Extremal Regions is similar to the MSER
in that suitable Extremal Regions (ERs) are selected from the whole component tree of the image.
However, this technique differs from MSER in that selection of suitable ERs is done by a sequential
classifier trained for character detection, i.e. dropping the stability requirement of MSERs and
@@ -88,9 +88,9 @@ order to increase the character localization recall.
After the ER filtering is done on each input channel, character candidates must be grouped in
high-level text blocks (i.e. words, text lines, paragraphs, ...). The opencv_text module implements
two different grouping algorithms: the Exhaustive Search algorithm proposed in [Neumann11] for
two different grouping algorithms: the Exhaustive Search algorithm proposed in @cite Neumann12 for
grouping horizontally aligned text, and the method proposed by Lluis Gomez and Dimosthenis Karatzas
in [Gomez13][Gomez14] for grouping arbitrary oriented text (see erGrouping).
in @cite Gomez13 @cite Gomez14 for grouping arbitrary oriented text (see erGrouping).
To see the text detector at work, have a look at the textdetection demo:
<https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/textdetection.cpp>