Recognition of Vietnamese sign language using MEMS accelerometers
نویسنده
چکیده
In this paper, we present work on understanding Vietnamese sign language through the use of Micro Electronic Mechanical System (MEMS) accelerometers. The system consists of six ADXL202 accelerometers for sensing the hand posture, a BASIC Stamp microcontroller and a PC for data acquisition and recognition of sign language. The data is then transformed to relative angles between fingers and the palm. Each character is recognized by a fuzzy rule based classification system, which allows the concept of vagueness in recognition. In addition, a set of Vietnamese spelling rules has been applied to improve the classification results.
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تاریخ انتشار 2005