Real-time Static Numeric Devnagari Sign Language Translator
Recognition of Numeric Devnagari Sign Language (DSL) using Hand Gesture Recognition System (HGRS) has become an essential tool for dump and deaf people to interact with commoners. The development of the proposed system Real-time Numeric Devnagari Sign Language Translator (RTNDSLT) is the significant objective of our research work. The system architecture of RTNDSLT system is mainly comprised of five phases arranged in layered fashion from top to bottom. Vision-based, real-time and static RTNDSLT system works in cluttered background with mixed lighting conditions. This system focuses on histogram recognition technique, centroid recognition technique, and fingertip recognition technique. RTDSLT is based on algorithms such as Histogram Recognition algorithm, Centroid Recognition algorithm, Peak-and-Valley Detection algorithm, and Peak-Point Detection algorithm along with Sample Image Database algorithm. RTNDSLT system achieves a detection rate of 94.13% by applying the approach of Two Hands and Single Camera along with fingertip recognition technique.
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 Baoyun Zhang, Ruwei Yun “Robust Gesture Recognition Based on Distance Distribution Feature and Skin-Color Segmentation”, Audio Language and Image Processing (ICALIP), 2010 International Conference on Signal Processing & Analysis, pp. 886- 891, doi: 10.1109/ICALIP.2010.5685201.
 Gang-Zeng Mao, Yi-Leh Wu, Maw-KaeHor, Cheng-Yuan Tang “Real-Time Hand Detection and Tracking against Complex Background”, Intelligent Information Hiding and Multimedia Signal Processing 2009 IIH-MSP '09, Fifth International Conference on Signal Processing & Analysis, pp. 905- 908, doi: 10.1109/IIH-MSP.2009.133.
 Yikai Fang, Kongqiao Wang, Jian Cheng and andHanqing Lu “A Real-Time Hand Gesture
 Syed AkhlaqHussain Shah, Ali Ahmed, IftekharMahmood and KhurramKhurshid, “Hand gesture Based User Interface for Computer Using Camera and Projector”, Signal and Image Processing Applications (ICSIPA), IEEE International Conference on Signal Processing & Analysis, 2011, pp. 168-173, doi: 10.1109/ICSIPA.2011.6144111.
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