半调图像的分类方法  

A classification method of halftone image

作　　者：文志强[1] 朱文球[1] 胡永祥[1] 

机构地区：[1]湖南工业大学计算机与通信学院,湖南株洲412007

出　　处：《山东大学学报（工学版）》2013年第4期7-12,共6页Journal of Shandong University（Engineering Science）

基　　金：国家自然科学基金资助项目(61170102);湖南省自然科学基金资助项目(11JJ3070;11JJ4050);湖南省教育厅科研资助项目(12A039)

摘　　要：针对半调模式的特点,提出有监督流形上的半调图像分类方法。该方法采取3个方向像素自相关特征和同或运算来描述纹理特征,利用图像分块的思想获取纹理特征,以利于提高建模效率和纹理特征的有效性。结合有监督学习和噪声样本点对模型、高维样本特征进行线性降维,以改善样本特征的可分性。在实验中分析建模方法的有效性,比较所提出方法与5个同类方法的分类性能并探讨了相关参数对分类性能的影响。实验结果表明,当K=32且L=8时,所提出得方法性能最好,且优于其它5个同类方法。A classification method of halftone image over supervised manifolds learning were proposed for classification of halftone image according to the characteristic of halftone pattern. The autocorrelation coefficient of pixel on three di- rection and XNOR operation were used to act as the descriptor of texture feature. A feature extraction based on image patches were presented for reducing modeling time and improving feature efficiency. To enhance the discriminating abil- ity of samples, the linear dimension reduction was conducted in high-dimensional feature space via supervised learning and creating model of noise sample pairs. In experiments, the efficiency problem of feature modeling was analyzed and the performance comparisons were conducted between the proposed method and five similar methods. The influences of the two parameters on classification performance were also discussed. Experiment results showed that our methods could get good classification performance if parameter K = 32 and L = 8 and was superior to other five classification methods.

关 键 词：半调图像 逆半调 特征建模 降维 分类 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]