一种改进的半调图像分类算法

半调图像分类在逆半调过程中是非常关键的步骤。文献[1]提出的神经网络分类算法利用增强的一维相关性,可以对半调图像进行适当的分类,但分类精度不够高。在神经网络分类算法的基础上,通过计算图像的灰度共生矩阵,进而提取图像的纹理特征来对图像进行分类。实验表明,改进后的算法可提高分类的精度。

Improved Algorithm for Halftone Image Classification

The classification of halftone image is a key step in the process of inverse halftone.The neural net classification Algorithm can classify the halftone images using the enhanced one-dimensional correlation of halftone images,but the precision is not very high.This paper based on the neural net classification algorithm abstract the textural features by calculate the gray level co-occurrence matrix of halftone images.Experimental results show that the improved algorithm can enhance the classification precision.