摘要
提出了一种图像特征融合新方法,应用于分析和挖掘图像中蕴含的丰富信息.基于神经网络学习功能构建图像特征与内涵之间的映射关系,达到挖掘图像内涵的目的.研究以文物图像为研究对象,选择了100幅古建筑图像,提取图像特征信息及其蕴含的语义信息,构建神经网络学习样本库,训练神经网络学习.实验选取了6幅测试样本,神经网络学习结果验证了本文方法的可行性和实用性.
A new method of image character fuse was used to analyze and mine a mass of information of image. The mapping between the image character and its meaning was established by using neural network learning to mine the meaning of image. The image of cultural heritage was taken as the object of this study, and the images of 100 ancient buildings were selected. Their image characters and semantic information were extracted, and learning base of neural network was established. The 6 test images were selected and validated the validity and practicability of this method.
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第12期62-65,共4页
Journal of Hunan University:Natural Sciences
基金
国家科技支撑计划资助项目(2006BAK31B03)
关键词
图像语义
特征提取
融合算法
神经网络
image semantic
character extraction
fuse algorithmic
neural network
