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Researchers in sign language recognition customized different sensors to capture hand signs. Gloves, digital cameras, depth cameras and Kinect were used alternatively in most systems. Due to signs closeness, input accuracy is a very essential constraint to reach a high recognition accuracy. Although previous systems accomplished high recognition accuracy,(More)
Many feature generation methods have been developed using pulse-coupled neural network. Most of these methods succeeded to achieve the invariance against object translation, rotation and scaling but could not neutralize the bright background effect and non-uniform light on the quality of the generated features. To overcome the shortcomings, the paper(More)
Automated translation systems for sign languages are important in a world that is showing a continuously increasing interest in removing barriers faced by physically challenged individuals in communicating and contributing to the society and the workforce. These systems can greatly facilitate the communication between the vocal and the nonvocal communities.(More)
In the early days Hydrocarbon wells were normally drilled vertically which rarely requires making decisions. As the technology progressed, the capability to do some deviation of the bit was used resulting in deviated or directional wells to follow the Hydrocarbon formation. This type of drilling requires real-time drilling directions decisions. In this(More)
  • A. S. Elons
  • 2014
Sign Language (SL) recognition has been explored for a long time now. Two main aspects of successful SL recognition systems are required: High recognition accuracy and real-time response. This paper shows a contribution in these issues, the first contribution describes a real-time response recognition for Arabic Sign Language (ArSL) based on a Graphics(More)
The lack of a visualized representation for standard Arabic Sign Language (ArSL) makes it difficult to do something as common place as looking up an unknown word in a dictionary. The majority of printed dictionaries organize ArSL signs (represented in drawings or pictures) based on their nearest Arabic translation; so unless one already knows the meaning of(More)