Abstract
Fingerspelling is used for words that have no sign, or for words that the sign is unknown. In this work, the signs of Turkish Alphabet are recognized from video images. The methods used are fast alignment, thick edge extraction and correlation with penalization methods. A 99 percent success ratio is achieved.
Keywords
Computer science
Turkish
Artificial intelligence
Sign (mathematics)
Correlation
Enhanced Data Rates for GSM Evolution
Feature extraction
Speech recognition
Alphabet
Pattern recognition (psychology)
Edge detection
Sign language
Computer vision
Mathematics
Image processing
Image (mathematics)
Geometry
Subject Areas
Hand Gesture Recognition Systems
·Human-Computer Interaction ·Physical Sciences
Advanced Image and Video Retrieval Techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
Human Pose and Action Recognition
·Computer Vision and Pattern Recognition ·Physical Sciences
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