DocumentCode :
2734669
Title :
Evaluation of features for automated transcription of dual-handed sign language alphabets
Author :
Lilha, Himanshu ; Shivmurthy, Devashish
Author_Institution :
Dept. of Comput. Sci. & Eng., PES Sch. of Eng., Bangalore, India
fYear :
2011
fDate :
3-5 Nov. 2011
Firstpage :
1
Lastpage :
5
Abstract :
Sign language helps the deaf and mute to communicate effectively. The paper demonstrates the evaluation of various feature extraction techniques for the dual -handed sign language alphabets. The efficiency of features like Histogram of Orientation Gradient (HOG) is discussed followed by the demonstration of the Histogram of Edge Frequency (HOEF) which overcomes the short coming of HOG. The evaluation of HOG accuracy is found to be 71.4% whereas with HOEF it is found to be 98.1%. The paper also demonstrate the overall system for the sign language recognition.
Keywords :
feature extraction; gesture recognition; automated dual-handed sign language alphabet transcription; feature evaluation; feature extraction techniques; histogram of edge frequency; histogram of orientation gradient; sign language recognition; Accuracy; Feature extraction; Handicapped aids; Histograms; Image edge detection; Information processing; Skin; HOEF; HOG; ISL; Sign language; dual-handed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Information Processing (ICIIP), 2011 International Conference on
Conference_Location :
Himachal Pradesh
Print_ISBN :
978-1-61284-859-4
Type :
conf
DOI :
10.1109/ICIIP.2011.6108943
Filename :
6108943
Link To Document :
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