Energy‐efficient adaptive optical character recognition for wearable devices
| Autor: | Seungjoo Son, Hyun So, Hyuk-Jun Lee, Joondong Kim, Dongkeon Choi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Power management
Computer science business.industry Real-time computing Mobile computing Wearable computer 020207 software engineering 02 engineering and technology Energy consumption Optical character recognition computer.software_genre ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering business Frequency scaling Mobile device computer Computer hardware Wearable technology Efficient energy use |
| Zdroj: | Electronics Letters. 52:113-115 |
| ISSN: | 1350-911X 0013-5194 |
| DOI: | 10.1049/el.2015.2959 |
| Popis: | As the computing power of mobile/wearable devices increases, computation-intensive real-time optical character recognition (OCR) becomes feasible for high-resolution images. Developing mobile/wearable OCR applications is challenging because they should perform highly accurate OCR within users' tolerable waiting time and achieve low energy consumption. An adaptive power management scheme is presented that predicts the execution time for OCR and minimises its energy consumption via dynamic voltage and frequency scaling while meeting its time constraint. Tesseract, a popular open source OCR engine, is used to verify the proposed scheme. The experimental results show up to 48.25% reduction in energy consumption (with an average reduction of 34.53%). |
| Databáze: | OpenAIRE |
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