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2020 | OriginalPaper | Buchkapitel

Text Detection Using Maximally Stable External Regions and Stroke Width Variation

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Abstract

There is a proverb “an image is worth, than ten thousand words”. So it is very difficult to explain a single image. But what happens if a single image itself contains some information in the form of text. Though it is easy to extract text from the structured image, it is difficult to retrieve it from unstructured image. Thus in this paper, we are providing an efficient and concrete algorithm to solve this problem. This algorithm consists of detecting candidate text region using maximally stable external regions (MSER). Then it removes false region based on basic geometric properties. Now, again removing false region based on stroke width variation (SWV) and finally merging all text regions for detection of the result. At last, recognition of detected text with the help of optical character recognition (OCR). All these methods are combined to give high performance of the proposed algorithm.

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Metadaten
Titel
Text Detection Using Maximally Stable External Regions and Stroke Width Variation
verfasst von
Nishant Singh
Vivek Kumar
Charul Bhatnagar
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-39875-0_38