Fingerspelling Recognition by Hand Shape Using Higher-Order Local Auto-Correlation Features
Fingerspelling Recognition by Hand Shape Using Higher-Order Local Auto-Correlation Features
摘要
The fingerspelling recognition by hand shape is an important step for developing a human-computer interaction system. A method of fingerspelling recognition by hand shape using HLAC （higher-order local auto-correlation） features is proposed. Furthermore, in order to use HLAC features more effectively, the use of image processing techniques： reducing an image resolution, dividing an image, and image pre-processing techniques, is also proposed. The experimental results show that the proposed method is promising.
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