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Sign language uses gestures instead of speech sounds to communicate. But in general, normal people rarely trying to learn sign language to interact with the deaf community. Recently, there are many sign language recognition system that had been developed. But most of them were implemented using desktop and laptop computer, which is impractical due to its weight and size. This paper presents a prototype...
Developing an automatic arabic sign language recognition system is of great importance, it can be used as a communication means between hearing-impaired and other people.
Cameras are embedded in many mobile/wearable devices and can be used for gesture recognition or even sign language recognition to help the deaf people communicate with others. In this paper, we proposed a vision-based gesture recognition system which can be used in environments with complex background. We design a method to adaptively update the skin color model for different users and various lighting...
The paper presents a comparison between different membership functions based type-1 fuzzy set for automatic hand gesture recognition for American Sign Language recognition. First pre-processing of the images is done using skin color based segmentation, morphological operations and to extract the hand gesture image from the background, Sobel edge detection technique is performed. Then the image is...
Gesture is one of the most vivid and dramatic way of communications between human and computer. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. This paper presents a hand gesture interface for controlling media player using neural network. The proposed algorithm recognizes a set of four specific...
Gesture is one of the most vivid and dramatic way of communications between human and computer. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. This paper presents a hand gesture interface for controlling media player using neural network. The proposed algorithm recognizes a set of four specific...
Communications between deaf-mute and a normal person have always been a challenging task. This paper describes a way to reduce barrier of communication by developing an assistive device for deaf-mute persons. The advancement in embedded systems, provides a space to design and develop a sign language translator system to assist the dumb people, there exist a number of assistant tools. The main objective...
This paper presents a real-time computer visionbased Bengali Sign Language (BdSL) recognition system. The system detects the probable hand from the captured image. The system uses Haar-like feature-based cascaded classifiers to detect the hand in each frame. From the detected hand area, the system extracts the hand sign based on Hue and Saturation value corresponding to human skin color. After normalization...
The proposed classifier is a novel skin detector that outperforms most of the existing approaches by dropping most of the non-skin pixels in its earlier stages of weak classifiers. Only the pixels with maximum skin likelihood are processed in later adaptive classifier. Parametric background modelling and validation based online training significantly improves the robustness of the whole classifier...
This paper introduces the gesture and hand posture tracking systems for a prototype real-time New Zealand sign language recognition system. The novelty of this work is in the markerless tracking of 13 gestures plus an unknown gesture category. Currently the gesture set is limited, but over time a more extensive gesture library can be developed and trained using the same technique. The hand posture...
In this paper, we propose an automatic system that recognizes both isolated and continuous gestures for Arabic numbers (0-9) in real-time based on hidden Markov model (HMM). To handle isolated gestures, HMM using ergodic, left-right (LR) and left-right banded (LRB) topologies with different number of states ranging from 3 to 10 is applied. Orientation dynamic features are obtained from spatio-temporal...
In the paper there is presented an efficient system for dynamic gesture recognition in movie sequences based on hidden Markov models. The system uses colour-based image segmentation methods and introduces high-dimensional feature vectors to more accurately describe hand shape in the picture. It also utilizes a-priori knowledge on gestures construction in order to allow effective dimensionality reduction,...
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