A demonstration for the detection of sign language. Issue 8 (17th November 2019)

• Record Type: Journal Article
• Authors: Purkayastha, Shauvik; Roy, Mridul Jyoti; Pradhan, Navam
• Is Part Of: Journal of information & optimization sciences. Volume 40:Issue 8(2019)
• Page Start: 1611
• Page End: 1621
• Publication Date: 2019-11-17
• Subjects: Computer Science; Preprocessing -- Opencv -- tensorflow -- matplotlib -- numpy -- convolutional neural networks; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2019.1704519
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: People having physical limitations such as speech and hearing impairment are often unable to convey their message properly, which leads to them being left out in many aspects of life. To help those people express themselves in a better and easier way we have developed the sign language detection application. We have developed a translator that takes hand gestures and input and give the equivalent alphabet as output, which will help those people to communicate. Convolutional neural network was used for image recognition and classification in order to detect the hand from other objects in the screen and classify the sign represented by the hand gesture at any given time, thus enabling us to translate the signs into English alphabets. Thus, this application can be used by the specially abled people to communicate with others in a more efficient and hassle freeway. The tools used were anaconda, python, Opencv, tensorflow, matplotlib, numpy, convolutional neural networks.