• Jasmine Kaur

To survive in the world, communication is the major requirement. Differently- abled people communicate among themselves using sign language but normal cannot use that same source of medium. In India the ratio of disability in seeing and hearing is 19% respectively with 8% having multiple disabilities. To bridge the communication gap of normal people and differently abled people, Sign Language Recognition System is one of the solutions. Extensive work has been done on Sign Language Recognition (SLR) for American data but Indian Sign Language Recognition (ISLR) differs significantly from American Sign Language Recognition (ASLR) system. In ISLR system human hand gestures, facial expressions, and lip movements are different type communication modes. This chapter focuses on the research work done so far, the machine learning and digital image processing techniques involved and how the steps lead to successful building of Indian Sign Language Recognition System for static images. It also introduces the image processing techniques required for the same. There are many descriptors and optimization techniques which have been used to create an efficient ISLR.

Indian Sign Language Recognition System (ISLR), American Sign Language Recognition System (ASLR), deaf and dumb, differently-abled people, machine learning, digital image processing

"CHAPTER 1: REVIEW PAPER ON ISLR TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 10, page no.406-415, October 2018, Available :http://www.jetir.org/papers/JETIRDQ06059.pdf

"CHAPTER 1: REVIEW PAPER ON ISLR TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 10, page no. pp406-415, October 2018, Available at : http://www.jetir.org/papers/JETIRDQ06059.pdf