A Simple Standalone Sign Based Recognition Translator without Using Super Computer Processing
In this paper, the design and development of a simple standalone sign based recognition translator without the use of supercomputer processing is presented. The main components for digital signal processing (DSP) and data storage in this translator system are peripheral interface controller (PIC) microcontroller and secure digital (SD) card respectively. The PIC 18F4620 is chosen as system’s DSP because it is able to interface with the SD card. The input of sign gestures is being recognized and translated into text message such that people can understand its meanings. A flex sensor is attached to each finger in a data glove which has the capability to measure the finger sign. The five fingers per hand can create many different signs that can be translated into different text messages. The attached PIC 18F4620 microcontroller in the data glove receives the data associated with a given sign. These data are then diagnosed and translated by matching with the predefined data in the SD card data storage device by using deterministic matching model. When the data is matched, the matched predefined data will be sent to the microcontroller to display its text message on an on-board LCD module. The developed standalone translating system is flexible and adaptive as it can be reprogrammable according to the users that have special disabilities without any aid from a supercomputer.
KeywordsSign language recognition system PIC microcontroller SD card
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- 1.Delin, A.: Disability in Context. Resource Disability Portfolio Guide 1. Resource: The Council for Museums, Archives and Libraries (2003) ISBN 1-903743-14-1Google Scholar
- 2.Poole, N.: Using Technology. Resource Disability Portfolio Guide 7. Resource: The Council for Museums, Archives and Libraries (2003) ISBN 1-903743-20-6Google Scholar
- 3.Hawkridge, D.G., Vincent, T., Hales, G.: New Information Technology in the Education of Disabled Children and Adults. College Hill Pr. (1985)Google Scholar
- 5.Mcguire, R.M., Hern, J., Starner, T., Henderson, V., Brashear, H., Ross, D.S.: Towards a One-Way American Sign Language Translator. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition (2004)Google Scholar
- 6.Vassilia, P.N., Konstantinos, M.G.: Listening to Deaf: A Greek Sign Language Translator. In: 2nd IEEE Information and Communication Technologies (ICTTA 2006), vol. 1, pp. 859–863 (2006)Google Scholar
- 7.Bilal, S., Akmeliawati, R., Shafie, A.A., Salami, M.J.E.: Hidden Markov Model for Human to Computer Interaction: A Study on Human Hand Gesture Recognition. Artificial Intelligence Review (2011), doi:10.1007/s10462-011-9292-0Google Scholar
- 10.Ibrahim, D.: Advanced PIC Microcontroller Projects in C: From USB to ZIGBEE with the PIC 18F Series. Newnes, Elsevier (2008)Google Scholar
- 11.SD Memory Card Specifications: Part 1 Physical Layer Specification. SD Group, Matsushita Electric Industrial Co., Ltd. (MEI), SanDisk Corporation, Toshiba Corporation, Version 1.01 (2001)Google Scholar
- 12.Borowik, B.: Interfacing PIC Microcontrollers to Peripherial Devices. Intelligent Systems, Control and Automation: Science and Engineering 49 (2011), doi:10.1007/978-94-007-1119-8_12Google Scholar