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Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network

Authors: AWODELE Oludele , Ogunsanwo Oyewole, Goga , & OKOLIE Samuel

Publication Type: Journal article

Journal: Internationaljournalofinformationandcommunicationsciences

ISSN Number:

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Abstract

Before the present study, no sign language recognition system for the Nigeria indigenous sign language
particularly Yoruba language has been developed. As a result, this research endeavors at introducing a Yoruba Sign Language
recognition system using image processing and Artificial Neural Network (ANN).The proposed system (YSLRS) was
implemented and tested. 600 images from 60 different signers were gathered. The images were acquired using vision based
method, the different signers were asked to stand in front of a laptop’s camera make sign number from one to ten with their
fingers in three different times and the images were stored in a folder. The image dataset was pre-processed for proper
presentation for de-noising, segmentation and feature extraction. Thereafter, pattern recognition was done using feed forward
back propagation ANN. The study revealed that Median filter with higher PSNR of 47.7 a lower MSE of 1.11, performed
better than the Gaussian filter. Furthermore, the efficiency of the developed system was determined using mean square error
and the best validation performance occurred at 25 epochs with a MSE of 0.004052, implying than ANN was able to
adequately recognize the pattern of the Yoruba signs. Histogram was also used to determine the efficiency of the system, it can
be seen that the histogram of the trained, tested and validated error bars were close to zero error, implying that the ANN and
Receiver Operating Characteristic (ROC) was used to evaluate the performance of ANN in matching the features of the Yoruba
Signs, which shows that ANN performed efficiently, having a high true positive rate and a minimum false positive rate.
Finally, YSLRS developed in the study would reduce negative attitudes of victimizations suffered by the hearing-impaired
individuals, by bridging communication gap among Nigerian PWD with hearing impairment.

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AWODELE,O. Ogunsanwo,G.O Goga,N. OKOLIE,S. . (2018). Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network, 3 (), 11-11.

AWODELE,O. Ogunsanwo,G.O Goga,N. OKOLIE,S. . "Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network" 3, no (), (2018): 11-11.

AWODELE,O. and Ogunsanwo,G.O and Goga,N. and OKOLIE,S. and . (2018). Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network, 3 (), pp11-11.

AWODELEO, OgunsanwoGO, GogaN, OKOLIES, . Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network. 2018, 3 ():11-11.

AWODELE,Oludele , Ogunsanwo,Gbenga Oyewole, Goga,Nicholas , and OKOLIE,Samuel . "Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network", 3 . (2018) : 11-11.

A.Oludele O.Gbenga Oyewole G.Nicholas & O.Samuel , "Bridging Communication Gap Among People with Hearing Impairment: An Application of Image Processing and Artificial Neural Network" vol.3, no., pp. 11-11, 2018.

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