Face and eye detection by CNN algorithms

被引:6
作者
Balya, D
Roska, T
机构
[1] Hungarian Acad Sci, Inst Comp & Automat, Analog & Neural Comp Lab, H-1111 Budapest, Hungary
[2] Tech Univ Budapest, H-1521 Budapest, Hungary
来源
JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY | 1999年 / 23卷 / 2-3期
关键词
D O I
10.1023/A:1008121908145
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
A novel approach to critical parts of face detection problems is given, based on analogic cellular neural network (CNN) algorithms. The proposed CNN algorithms find and help to normalize human faces effectively while their time requirement is a fraction of the previously used methods. The algorithm starts with the detection of heads on color pictures using deviations in color and structure of the human face and that of the background. By normalizing the distance and position of the reference points, all faces should be transformed into the same size and position. For normalization, eyes serve as points of reference. Other CNN algorithm finds the eyes on any grayscale image by searching characteristic features of the eyes and eye sockets. Tests made on a standard database show that the algorithm works very fast and it is reliable.
引用
收藏
页码:497 / 511
页数:15
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