6,745 research outputs found
Efficient Scene Text Localization and Recognition with Local Character Refinement
An unconstrained end-to-end text localization and recognition method is
presented. The method detects initial text hypothesis in a single pass by an
efficient region-based method and subsequently refines the text hypothesis
using a more robust local text model, which deviates from the common assumption
of region-based methods that all characters are detected as connected
components.
Additionally, a novel feature based on character stroke area estimation is
introduced. The feature is efficiently computed from a region distance map, it
is invariant to scaling and rotations and allows to efficiently detect text
regions regardless of what portion of text they capture.
The method runs in real time and achieves state-of-the-art text localization
and recognition results on the ICDAR 2013 Robust Reading dataset
Object Proposals for Text Extraction in the Wild
Object Proposals is a recent computer vision technique receiving increasing
interest from the research community. Its main objective is to generate a
relatively small set of bounding box proposals that are most likely to contain
objects of interest. The use of Object Proposals techniques in the scene text
understanding field is innovative. Motivated by the success of powerful while
expensive techniques to recognize words in a holistic way, Object Proposals
techniques emerge as an alternative to the traditional text detectors.
In this paper we study to what extent the existing generic Object Proposals
methods may be useful for scene text understanding. Also, we propose a new
Object Proposals algorithm that is specifically designed for text and compare
it with other generic methods in the state of the art. Experiments show that
our proposal is superior in its ability of producing good quality word
proposals in an efficient way. The source code of our method is made publicly
available.Comment: 13th International Conference on Document Analysis and Recognition
(ICDAR 2015
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