The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of COMPUTERS
Transactions ID Number: 19-889
Full Name: Iyad Aldasoqui
Position: Engineer
Age: ON
Sex: Male
Address: P.O.Box 1438
Country: JORDAN
Tel: 00962777488955
Tel prefix:
Fax:
E-mail address: iyad@rss.gov.jo
Other E-mails: iyadmaster@gmail.com
Title of the Paper: Smart Human Face Detection System
Authors as they appear in the Paper: Iyad Aldasouqi, and Mahmoud Hassan
Email addresses of all the authors: iyad@rss.gov.jo, m.hassan@psut.edu.jo
Number of paper pages: 8
Abstract: Digital Image Processing (DIP) is a multidisciplinary science that borrows principles from diverse fields such as optics, surface physics, visual psychophysics, computer science and mathematics. Some of image processing applications can be finding in: astronomy, ultrasonic imaging, remote sensing, video communications and microscopy. Face detection/recognition has attracted much attention and its research has rapidly increased in many potential applications in computer, communication and automatic access control system. Furthermore, face detection as a first step is an important part of face recognition. Since the image has lots of variations in appearance, face detection is not straightforward, such as pose variation, occlusion, image orientation, illuminating condition and others. The full face detection and gender recognition system is made up of a series of connected components. There are much software that can facilitate the detection process such as: Matla!
b, Labview, C# and others. In this paper we propose a fast algorithm for detecting human faces in color images using HSV color model without sacrificing the speed of detection. The proposed algorithm has been tested on various real images and its performance is found to be quite satisfactory.
Keywords: Face detection, Color , Skin detection, Image processing, Skin color.
EXTENSION of the file: .doc
Special (Invited) Session: Human Face Detection System Using HSV
Organizer of the Session: 104-797
How Did you learn about congress:
IP ADDRESS: 193.188.73.1
