Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

SEDIQA: Sound Emitting Document Image Quality Assessment in a Reading Aid for the Visually Impaired

Version 1 : Received: 7 July 2021 / Approved: 8 July 2021 / Online: 8 July 2021 (13:21:49 CEST)

How to cite: Courtney, J. SEDIQA: Sound Emitting Document Image Quality Assessment in a Reading Aid for the Visually Impaired. Preprints 2021, 2021070200 (doi: 10.20944/preprints202107.0200.v1). Courtney, J. SEDIQA: Sound Emitting Document Image Quality Assessment in a Reading Aid for the Visually Impaired. Preprints 2021, 2021070200 (doi: 10.20944/preprints202107.0200.v1).

Abstract

For Visually impaired People (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in Optical Character Recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue – the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function – no small task for VIPs. In this work, a Sound-Emitting Document Image Quality Assessment metric (SEDIQA) is proposed which allows the user to hear the quality of the text image and automatically captures the best image for OCR accuracy. This work also includes testing of OCR performance against image degradations, to identify the most significant contributors to accuracy reduction. The proposed No-Reference Image Quality Assessor (NR-IQA) is validated alongside established NR-IQAs and this work includes insights into the performance of these NR-IQAs on document images.

Subject Areas

image quality assessment; image quality metrics; NR-IQAs; D-IQA; OCR accuracy; OCR prediction; OCR improvements; visual aids; visually impaired; reading aids; document images; text-based images

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