Title :
Cranio-maxillo-facial Image Date Fusion Based on RBF Neural Network
Author :
Liwen Huang ; Ke Pang ; Xin Wang ; Tao Wang ; Wannian Chui
Author_Institution :
Electron. Inf. & Autom., Chongqing Univ. of Technol., Chongqing, China
Abstract :
This paper analyzes a new biological object cranio-maxillo-facial image and set the shape feature and texture features as invariant moments. In this paper we use wavelet packet extract texture features. After the extraction of cranio-maxillo-facial multi-feature information, RBF neural network is used to be the diverse characteristics of the craniofacial data fusion and recognition judgment. The experimental results show that information fusion algorithm based on RBF neural network can effectively identify cranio-maxillo-facial individuals and have high recognition accuracy than single characteristic.
Keywords :
diagnostic radiography; feature extraction; image fusion; image recognition; image texture; medical image processing; radial basis function networks; wavelet transforms; RBF neural network; biological object; cranio-maxillo-facial image date fusion; cranio-maxillo-facial multifeature information; feature extraction; invariant moments; radial basis function network; recognition accuracy; recognition judgment; shape feature; texture feature; wavelet packet; Feature extraction; Libraries; Neural networks; Shape; Training; Wavelet packets; Cranio-maxillo-facial; Data fusion; RBF neural network; Shape feature; Texture feature;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location :
Hangzhou
DOI :
10.1109/ISCID.2013.58