Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language

S. T. Hassan; J. A. Abolarinwa; C. O. Alenoghena; S. A. Bala; M. David; Ali Farzaminia

doi:10.1109/I2CACIS.2017.8239041

Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language

S. T. Hassan, J. A. Abolarinwa, C. O. Alenoghena, S. A. Bala, M. David, Ali Farzaminia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

Hausa sign language (HSL) is the main communication medium among deaf-mute Hausas in northern Nigeria. HSL is so unique that a deaf-mute individual from other part of the country can rarely understand it. HSL includes static and dynamic hand gesture recognitions. In this paper we present an intelligent recognition of static, manual and nonmanual HSL using an enhanced Fourier descriptor. A Red Green Blue (RGB) digital camera was used for image acquisition and Fourier descriptor was used for features extraction. The features extracted chosen manually and fed into artificial neural network (ANN) which was used for classification. Thereafter particle swarm optimization algorithm (PSO) was used to optimize the features based on their fitness in order to obtain high recognition accuracy. The optimized features selected gave a higher recognition accuracy of 90.5% compared to the manually selected features that gave 74.8% accuracy. High average recognition accuracy was achieved; hence, intelligent recognition of HSL was successful.

Original language	English
Title of host publication	Proceedings - 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	104-109
Number of pages	6
ISBN (Electronic)	9781538608463, 9781538608456
ISBN (Print)	9781538608470
DOIs	https://doi.org/10.1109/I2CACIS.2017.8239041
Publication status	Published - 25 Dec 2017
Externally published	Yes
Event	2nd IEEE International Conference on Automatic Control and Intelligent Systems - Kota Kinabalu, Sabah, Malaysia Duration: 21 Oct 2017 → 21 Oct 2017 Conference number: 2

Conference

Conference	2nd IEEE International Conference on Automatic Control and Intelligent Systems
Abbreviated title	I2CACIS 2017
Country/Territory	Malaysia
City	Kota Kinabalu, Sabah
Period	21/10/17 → 21/10/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Hassan, S. T., Abolarinwa, J. A., Alenoghena, C. O., Bala, S. A., David, M., & Farzaminia, A. (2017). Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language. In Proceedings - 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017 (pp. 104-109). [8239041] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/I2CACIS.2017.8239041

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title = "Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language",

abstract = "Hausa sign language (HSL) is the main communication medium among deaf-mute Hausas in northern Nigeria. HSL is so unique that a deaf-mute individual from other part of the country can rarely understand it. HSL includes static and dynamic hand gesture recognitions. In this paper we present an intelligent recognition of static, manual and nonmanual HSL using an enhanced Fourier descriptor. A Red Green Blue (RGB) digital camera was used for image acquisition and Fourier descriptor was used for features extraction. The features extracted chosen manually and fed into artificial neural network (ANN) which was used for classification. Thereafter particle swarm optimization algorithm (PSO) was used to optimize the features based on their fitness in order to obtain high recognition accuracy. The optimized features selected gave a higher recognition accuracy of 90.5% compared to the manually selected features that gave 74.8% accuracy. High average recognition accuracy was achieved; hence, intelligent recognition of HSL was successful.",

keywords = "Artificial Neural Network, Fourier Descriptor, Hausa Sign Language, Particle Swarm Optimization Algorithm",

author = "Hassan, {S. T.} and Abolarinwa, {J. A.} and Alenoghena, {C. O.} and Bala, {S. A.} and M. David and Ali Farzaminia",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2nd IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017 ; Conference date: 21-10-2017 Through 21-10-2017",

year = "2017",

month = dec,

day = "25",

doi = "10.1109/I2CACIS.2017.8239041",

language = "English",

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Hassan, ST, Abolarinwa, JA, Alenoghena, CO, Bala, SA, David, M & Farzaminia, A 2017, Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language. in Proceedings - 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017., 8239041, Institute of Electrical and Electronics Engineers Inc., pp. 104-109, 2nd IEEE International Conference on Automatic Control and Intelligent Systems, Kota Kinabalu, Sabah, Malaysia, 21/10/17. https://doi.org/10.1109/I2CACIS.2017.8239041

Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor : A Case of Hausa Sign Language. / Hassan, S. T.; Abolarinwa, J. A.; Alenoghena, C. O. et al.

Proceedings - 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 104-109 8239041.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor

T2 - 2nd IEEE International Conference on Automatic Control and Intelligent Systems

AU - Hassan, S. T.

AU - Abolarinwa, J. A.

AU - Alenoghena, C. O.

AU - Bala, S. A.

AU - David, M.

AU - Farzaminia, Ali

N1 - Conference code: 2

PY - 2017/12/25

Y1 - 2017/12/25

N2 - Hausa sign language (HSL) is the main communication medium among deaf-mute Hausas in northern Nigeria. HSL is so unique that a deaf-mute individual from other part of the country can rarely understand it. HSL includes static and dynamic hand gesture recognitions. In this paper we present an intelligent recognition of static, manual and nonmanual HSL using an enhanced Fourier descriptor. A Red Green Blue (RGB) digital camera was used for image acquisition and Fourier descriptor was used for features extraction. The features extracted chosen manually and fed into artificial neural network (ANN) which was used for classification. Thereafter particle swarm optimization algorithm (PSO) was used to optimize the features based on their fitness in order to obtain high recognition accuracy. The optimized features selected gave a higher recognition accuracy of 90.5% compared to the manually selected features that gave 74.8% accuracy. High average recognition accuracy was achieved; hence, intelligent recognition of HSL was successful.

AB - Hausa sign language (HSL) is the main communication medium among deaf-mute Hausas in northern Nigeria. HSL is so unique that a deaf-mute individual from other part of the country can rarely understand it. HSL includes static and dynamic hand gesture recognitions. In this paper we present an intelligent recognition of static, manual and nonmanual HSL using an enhanced Fourier descriptor. A Red Green Blue (RGB) digital camera was used for image acquisition and Fourier descriptor was used for features extraction. The features extracted chosen manually and fed into artificial neural network (ANN) which was used for classification. Thereafter particle swarm optimization algorithm (PSO) was used to optimize the features based on their fitness in order to obtain high recognition accuracy. The optimized features selected gave a higher recognition accuracy of 90.5% compared to the manually selected features that gave 74.8% accuracy. High average recognition accuracy was achieved; hence, intelligent recognition of HSL was successful.

KW - Artificial Neural Network

KW - Fourier Descriptor

KW - Hausa Sign Language

KW - Particle Swarm Optimization Algorithm

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U2 - 10.1109/I2CACIS.2017.8239041

DO - 10.1109/I2CACIS.2017.8239041

M3 - Conference contribution

AN - SCOPUS:85048204642

SN - 9781538608470

SP - 104

EP - 109

BT - Proceedings - 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 21 October 2017 through 21 October 2017

ER -

Hassan ST, Abolarinwa JA, Alenoghena CO, Bala SA, David M, Farzaminia A. Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language. In Proceedings - 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems, I2CACIS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 104-109. 8239041 doi: 10.1109/I2CACIS.2017.8239041

Intelligent Sign Language Recognition Using Enhanced Fourier Descriptor: A Case of Hausa Sign Language

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