期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2017
卷号：9
期号：07
页码：466-471
出版社：Engg Journals Publications
摘要：The paper aims to propose a novel technique that recognizes finger spelled American Sign Language (ASL) gestures. The external characteristic of hand, i.e. shape based algorithm is being used for recognition. Since almost all of the alphabets have a unique shape, each alphabet is characterized on the basis landmark points marked on the boundary of the hand shown by the signer. A training set is made by training several images of each alphabet and the landmark points of each alphabet which produces a 72 point descriptor are stored in database. The descriptor of test image is then matched with the ones in database. Finally, Euclidean distance classifies the test images to the recognized alphabet. By increasing the number of sampling points there was an increase in accuracy rate. Thus a 180 point descriptor results in better recognition.
关键词：Fingerspelling ASL; external characteristics; landmark; training set; descriptor; Euclidean distance.
