A Note of Fingerspelling Recognition by Hand Shape Using Higher-Order Local Auto-Correlation Features

被引：0
|
作者：
Kanemura, Takuya [1 ]
Mitani, Yoshihiro [1 ]
Fujita, Yusuke [2 ]
Hamamoto, Yoshihiko [2 ]
机构：
[1] Ube Natl Coll Technol, Ube, Yamaguchi 7558555, Japan
[2] Yamaguchi Univ, Fac Engn, Ube, Yamaguchi 7558611, Japan
来源：
2012 PROCEEDINGS OF SICE ANNUAL CONFERENCE (SICE) | 2012年
关键词：
Image Processing Techniques; Fingerspelling Recognition by Hand Shape; HLAC features; Division of an Image;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
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 higher-order local auto-correlation(HLAC) features is proposed. From the experimental results, the proposed method is promising. And to redeuce image resolution and to thresholding an image are shown to be effective. In this paper, in order to further improve the fingerspelling recognition performance, we have proposed the use of division of an image in extracting HLAC features. The results show that the division of an image is effective for fingerspelling recognition by hand shape.
引用
收藏
页码：777 / +
页数：2
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