Search results

1 – 1 of 1
To view the access options for this content please click here
Article
Publication date: 6 May 2014

Yong-Hwan Lee, Hyochang Ahn, Han-Jin Cho and June-Hwan Lee

This paper holds a big advantage to enable to recognize faces, regardless of time and place. Also this provides an independent performance of smart phone, because of its…

Abstract

Purpose

This paper holds a big advantage to enable to recognize faces, regardless of time and place. Also this provides an independent performance of smart phone, because of its process by a computer of third party not by that of the mobile device. In addition, it is desirable to minimize the expensive operations in mobile device with constraint computational power (i.e. battery consumption). Thus, the authors exclude the process of transmission failed from the input device. The paper aims to discuss these issues.

Design/methodology/approach

In this paper, the authors have proposed a new face detection and verification algorithm, based on skin color detection to enable extracting the face region from color images of the mobile phone. And then extracted the facial feature as eigenface, verified whether or not the identity of users is right, applied support vector machine to the region of detected face.

Findings

The experimental results for two datasets show that the proposed method achieves slightly higher efficiencies at the detection and verification of user identity, compared with other method, where varying lighting conditions with complex backgrounds, according to be fast and accurate than any other previous methods.

Originality/value

The proposed algorithm enables to implement fast and accurate search using triangle-square transformation for detection of human faces in a digital still color images, obtained by the mobile device camera under unconstraint environments, using advanced skin color model and characteristic points in a detected face.

Details

Journal of Systems and Information Technology, vol. 16 no. 2
Type: Research Article
ISSN: 1328-7265

Keywords

1 – 1 of 1