期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN:2158-107X
电子版ISSN:2156-5570
出版年度:2013
卷号:4
期号:2
DOI:10.14569/IJACSA.2013.040228
出版社:Science and Information Society (SAI)
摘要:Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Extraction and Classification. 24 signs were considered in this paper, each having 10 samples, thus a total of 240 images was considered for which recognition rate obtained was 97%.
关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Hand Gesture Recognition; Skin Filtering; Human Computer Interaction; Euclidean Distance (E.D.); Eigen value; Eigen vector.