scholarly journals Jaundice in Newborn Monitoring using Color Detection Method

2012 ◽  
Vol 29 ◽  
pp. 1631-1635 ◽  
Author(s):  
M.N. Mansor ◽  
S. Yaacob ◽  
M. Hariharan ◽  
S.N. Basah ◽  
S.H.F.S. Ahmad Jamil ◽  
...  
2006 ◽  
Vol 06 (01) ◽  
pp. 115-124 ◽  
Author(s):  
QING-FANG ZHENG ◽  
WEI ZENG ◽  
WEI-QIANG WANG ◽  
WEN GAO

This paper investigates adult images detection based on the shape features of skin regions. In order to accurately detect skin regions, we propose a skin detection method using multi-Bayes classifiers in the paper. Based on skin color detection results, shape features are extracted and fed into a boosted classifier to decide whether or not the skin regions represent a nude. We evaluate adult image detection performance using different boosted classifiers and different shape descriptors. Experimental results show that classification using boosted C4.5 classifier and combination of different shape descriptors outperforms other classification schemes.


2014 ◽  
Vol 490-491 ◽  
pp. 1259-1266 ◽  
Author(s):  
Muralindran Mariappan ◽  
Manimehala Nadarajan ◽  
Rosalyn R. Porle ◽  
Vigneswaran Ramu ◽  
Brendan Khoo Teng Thiam

Biometric identification has advanced vastly since many decades ago. It became a blooming area for research as biometric technology has been used extensively in areas like robotics, surveillance, security and others. Face technology is more preferable due to its reliability and accuracy. By and large, face detection is the first processing stage that is performed before extending to face identification or tracking. The main challenge in face detection is the sensitiveness of the detection to pose, illumination, background and orientation. Thus, it is crucial to design a face detection system that can accommodate those problems. In this paper, a face detection algorithm is developed and designed in LabVIEW that is flexible to adapt changes in background and different face angle. Skin color detection method blending with edge and circle detection is used to improve the accuracy of face detected. The overall system designed in LabVIEW was tested in real time and it achieves accuracy about 97%.


2012 ◽  
Vol 29 ◽  
pp. 1625-1630
Author(s):  
M.N. Mansor ◽  
S. Yaacob ◽  
M. Hariharan ◽  
S.N. Basah ◽  
S.H.F.S. Ahmad Jamil ◽  
...  

2011 ◽  
Vol 31 (5) ◽  
pp. 1233-1236
Author(s):  
Xia XIONG ◽  
Qing-bing SANG

Sign in / Sign up

Export Citation Format

Share Document