【24h】

Print image sharpness analysis based on gray-level co-occurrence matrices

机译:基于灰度共现矩阵的打印图像清晰度分析

获取原文

摘要

A novel measure is presented to quantify print image sharpness. Nine texture features of gray level co-occurrence matrices (GLCM) were calculated from the print images respectively which were blurred by Gaussian blurs filter with different radius ranging from 0 to 8 pixels in steps of 2. Experiments were performed on these images with different GLCM distance d (2, 4, 6, 8,10 pixels) and orientation 0 (0°, 45°, 90°, 135°) under the constant window size (64 pixels). Furthermore, the correlation matrix of texture features was calculated to judge which texture features can be chosen to assess sharpness most. The test results show contrast and energy provide the most unique information of print image sharpness. And the distance d of GLCM can be determined to be 6 pixels and the different orientation 9 has little effect on the trends. The method is reliable and extends GLCM with the sharpness evaluation of variable size, oriented print image.
机译:提出了一种新颖的方法来量化打印图像的清晰度。分别从打印图像中计算出9个灰度共生矩阵(GLCM)的纹理特征,这些图像通过高斯模糊滤镜进行了模糊处理,半径从0到8像素不等,步长为2。固定窗口大小(64个像素)下的距离d(2、4、6、8、10像素)和方向0(0°,45°,90°,135°)。此外,计算了纹理特征的相关矩阵,以判断可以选择哪些纹理特征来最评估清晰度。测试结果表明对比度和能量提供了打印图像清晰度的最独特信息。 GLCM的距离d可以确定为6个像素,而不同的方向9对趋势的影响很小。该方法是可靠的,并且通过可变尺寸,定向打印图像的清晰度评估扩展了GLCM。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号