Bahare Jalilian

Work place: Department of Computer Engineering, Kermanshah Science and Research Branch, Islamic Azad University Kermanshah, Iran



Research Interests: Computer systems and computational processes, Computer Vision, Pattern Recognition, Image Processing


Bahare Jalilian, She is currently working toward the M.Sc. degree in the Islamic Azad University, Kermanshah Science and Research Branch. She obtained her B.S. in Computer Engineering from Razi University of Kermanshah, Iran in 2011. Her research interests include computer vision, digital image processing and pattern recognition.

Author Articles
Persian Sign Language Recognition Using Radial Distance and Fourier Transform

By Bahare Jalilian Abdolah Chalechale

DOI:, Pub. Date: 8 Nov. 2013

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.

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