期刊
PROCEEDINGS OF 12TH IAPR WORKSHOP ON DOCUMENT ANALYSIS SYSTEMS, (DAS 2016)
卷 -, 期 -, 页码 428-433出版社
IEEE COMPUTER SOC
DOI: 10.1109/DAS.2016.57
关键词
Mid Level Features; Script Identification; Scene Text
We present an approach for automatically identifying the script of the text localized in the scene images. Our approach is inspired by the advancements in mid-level features. We represent the text images using mid-level features which are pooled from densely computed local features. Once text images are represented using the proposed mid-level feature representation, we use an off-the-shelf classifier to identify the script of the text image. Our approach is efficient and requires very less labeled data. We evaluate the performance of our method on a recently introduced CVSI dataset, demonstrating that the proposed approach can correctly identify script of 96.70% of the text images. In addition, we also introduce and benchmark a more challenging Indian Language Scene Text (ILST) dataset for evaluating the performance of our method.
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