Persian Sign Language Recognition Using Radial Distance and Fourier Transform

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Bahare Jalilian 1,* Abdolah Chalechale 2

1. Department of Computer Engineering, Kermanshah Science and Research Branch, Islamic Azad University Kermanshah, Iran

2. Department of Computer Engineering, Razi University Kermanshah, Iran

* Corresponding author.


Received: 10 Jul. 2013 / Revised: 15 Aug. 2013 / Accepted: 27 Sep. 2013 / Published: 8 Nov. 2013

Index Terms

Persian sign language, hand gesture recognition, Guassian model, centroid distance, Fourier transform, Euclidean distance


This paper provides a novel hand gesture recognition method to recognize 32 static signs of the Persian Sign Language (PSL) alphabets. Accurate hand segmentation is the first and important step in sign language recognition systems. Here, we propose a method for hand segmentation that helps to build a better vision based sign language recognition system. The proposed method is based on YCbCr color space, single Gaussian model and Bayes rule. It detects region of hand in complex background and non-uniform illumination. Hand gesture features are extracted by radial distance and Fourier transform. Finally, the Euclidean distanceis used to compute the similarity between the input signs and all training feature vectors in the database. The system is tested on 480 posture images of the PSL, 15 images for each 32 signs. Experimental results show that our approach is capable to recognize all 32 PSL alphabets with 95.62% recognition rate.

Cite This Paper

Bahare Jalilian, Abdolah Chalechale,"Persian Sign Language Recognition Using Radial Distance and Fourier Transform", IJIGSP, vol.6, no.1, pp.40-46, 2014. DOI: 10.5815/ijigsp.2014.01.06


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