• Corpus ID: 212515731

Real Time Static Hand Gesture Recognition System in Complex Background that uses Number system of Indian Sign Language

  title={Real Time Static Hand Gesture Recognition System in Complex Background that uses Number system of Indian Sign Language},
  author={Jayshree Pansare and Hrushikesh Dhumal and Sanket Babar and Kiran Sonawale and Ajit Sarode},
Hand gestures are powerful means of communication among humans and sign language is the most natural and expressive way of communication for deaf and mute people. Communication between computers (or robot) and humans, just as we humans interact with one another has been the prime objective of human computer interaction (HCI) research. This paper describes a real-time system for human computer interaction through gesture recognition for Indian Sign Language (ISL). ISL number system includes nine… 

Figures from this paper

A novel hand segmentation method for multiple-hand gesture recognition system under complex background
This paper presents a robust and effective method of hand segmentation which overcomes problems such as skin color detection, complex background removal, complexity from multiple gesturers in front of the camera and variable lighting condition.
Vision-based approach for American Sign Language recognition using Edge Orientation Histogram
  • J. Pansare, M. Ingle
  • Computer Science
    2016 International Conference on Image, Vision and Computing (ICIVC)
  • 2016
Proposed Real-time static Alphabet American Sign Language Recognizer- (A-ASLR) is designed for the recognition of ASL alphabets into their translated version in text (i.e. A to Z) and achieves the recognition rate of 88.26% within recognition time of 0.5 second in complex background with mixed lightning condition.
Real-time Static Numeric Devnagari Sign Language Translator
The proposed system Realtime Numeric Devnagari Sign Language Translator (RTNDSLT) 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.
A Conditional Random Field Based Indian Sign Language Recognition System under Complex Background
A Conditional Random Field (CRF) based Indian Sign Language (ISL) recognition system which is effective under complex background using a novel set of features and efficient and robust hand segmentation and tracking algorithm to achieve better recognition rates.
International Journal of Scientific Research in Computer Science, Engineering and Information Technology
This work is on the development of the proposed system Real-time Numeric Devnagari Sign Language Translator (RTNDSLT), which achieves a recognition rate of 94.13% using Two Hands Single Camera approach and fingertip recognition technique.
Control of Electronic Appliances by Hand Gesture Recognition System
The proposed system here is far more advance to the existing system and it uses the HCI concepts, hand gesture recognition to control over the electronic appliances.
Comprehensive Performance Study of Existing Techniques in Hand Gesture Recognition System for Sign Languages
This study is presented on the basis of fragmentation used in HGRS and includes the strength and the scope of improvements for each technique and will be highly useful to the researchers putting efforts in the domain of recognition of sign languages for improving the recognition rate particularly.


Real-Time Static Hand Gesture Recognition for American Sign Language (ASL) in Complex Background
This gesture recognition system can reliably recognize single-hand gestures in real time and can achieve a 90.19% recognition rate in complex background with a “minimum-possible constraints” approach.
Hand region extraction and gesture recognition from video stream with complex background through entropy analysis
A method to recognize band gestures extracted from images with a complex background for a more natural interface in HCI (human computer interaction), which obtains the image by subtracting one image from another sequential image, measures the entropy, separates hand region from images, tracks the hand region and recognizes hand gestures.
Human computer interface for gesture-based editing system
Experimental results demonstrate that the proposed HMM for alphabetical hand gesture recognition yields a higher and satisfying recognition rate with various gestures.
Hand Segmentation Techniques to Hand Gesture Recognition for Natural Human Computer Interaction
Hand tracking and segmentation algorithm (HTS) is found to be most efficient to handle the challenges of vision based system such as skin color detection, complex background removal and variable lighting condition.
Gesture-based interaction and communication: automated classification of hand gesture contours
A complete vision-based system, consisting of hand gesture acquisition, segmentation, filtering, representation and classification, is developed to robustly classify hand gestures and it is estimated that real-time gesture classification is possible through the use of a high- Speed PC, high-speed digital signal processing chips and code optimization.
Inner distance based hand gesture recognition for devices control
In tracking phase, a new method based on hand center of gravity tracking and in recognition phase, the method uses correlation coefficient for state matching.
Vision based gesture recognition system with single camera
  • Wei-Hau Du, Hua Li
  • Computer Science
    WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000
  • 2000
A real-time system for human-computer interaction through gesture recognition and hand tracking that recognizes the hand gesture with just one camera, thus avoiding the problem of matching image features between different views.
Two Hand Tracking Using Colour Statistical Model with the K-means Embedded Particle Filter for Hand Gesture Recognition
This work presents the enhanced tracking of two hands based on a statistical model using only a skin colour feature with particle filtering for gesture recognition and shows that adaptive use of the scheme provides improvement compared to use with other techniques such as mean-shift tracking.
Designing of Human Computer Interactive Platform for Robotic Applications
A system which enables a robot to recognize and respond to hand gestures from a human operator and demonstrate that the proposed HCI platform can be used reliably in robotic applications is described.
Computational Vision and Active Perception Laboratory, CVAP
The CVAP (Computational Vision and Perception Laboratory) performs research in computer vision and robotics since 1982 and is a partner in two consortia sponsored by SSF, CAS: The Center for Autonomous Systems, and VISIT: Visual Information Technology.