Quranic Sign Language for Deaf People: Quranic Recitation Classification and Verification
AbstractThis paper provides an overview of the techniques used in image and video recognition for sign language through following hand motions and translating it to the text of the Holy Quran. It also provides a proposal for a system that will be capable of identifying errors in Quran recitation depending on alphabets of Arabic and Quranic sign language and be able to show where exactly errors have occurred. In addition, this system will identify and classify location of verse (Ayah) and names of Souras depending on Back Propagation technique of the neural network.
How to Cite
Mahmod, M. A., & Zeki, A. (2018). Quranic Sign Language for Deaf People: Quranic Recitation Classification and Verification. International Journal on Perceptive and Cognitive Computing, 4(1), 7–11. https://doi.org/10.31436/ijpcc.v4i1.54