A note of fingerspelling recognition by hand shape using higher-order local auto-correlation features

Author

Kanemura, Takuya ; Mitani, Yoshihiro ; Fujita, Yusuke ; Hamamoto, Yoshihiko

Author_Institution

Ube Nat. Coll. of Technol., Ube, Japan

fYear

2012

fDate

20-23 Aug. 2012

Firstpage

777

Lastpage

778

Abstract

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 reduce 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.

Keywords

correlation methods; feature extraction; gesture recognition; human computer interaction; image resolution; image segmentation; HLAC feature extraction; fingerspelling recognition performance improvement; hand shape; higher-order local autocorrelation feature extraction; human-computer interaction system; image resolution reduction; image thresholding; Educational institutions; Error analysis; Feature extraction; Image recognition; Pattern recognition; Shape; Training; Division of an Image; Fingerspelling Recognition by Hand Shape; HLAC features; Image Processing Techniques;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE Annual Conference (SICE), 2012 Proceedings of

Conference_Location

Akita

ISSN

pending

Print_ISBN

978-1-4673-2259-1

Type

conf

Filename

6318544