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Microscale halftone color image analysis: perspective of spectral color prediction modeling

机译:微型半色调彩色图像分析:光谱颜色预测建模的角度

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A method has been proposed, whereby k-means clustering technique is applied to segment microscale single color halftone image into three components-solid ink, ink/paper mixed area and unprinted paper. The method has been evaluated using impact (offset) and non-impact (electro-photography) based single color prints halftoned by amplitude modulation (AM) and frequency modulation (FM) technique. The print samples have also included a range of variations in paper substrates. The colors of segmented regions have been analyzed in CIELAB color space to reveal the variations, in particular those present in mixed regions. The statistics of intensity distribution in the segmented areas have been utilized to derive expressions that can be used to calculate simple thresholds. However, the segmented results have been employed to study dot gain in comparison with traditional estimation technique using Murray-Davies formula. The performance of halftone reflectance prediction by spectral Murray-Davies model has been reported using estimated and measured parameters. Finally, a general idea has been proposed to expand the classical Murray-Davies model based on experimetal observations. Hence, the present study primarily presents the outcome of experimental efforts to characterize halftone print media interactions in respect to the color prediction models. Currently, most regression-based color prediction models rely on mathematical optimization to estimate the parameters using measured average reflectance of a large area compared to the dot size. While this general approach has been accepted as a useful tool, experimental investigations can enhance understanding of the physical processes and facilitate exploration of new modeling strategies. Furthermore, reported findings may help reduce the required number of samples that are printed and measured in the process of multichannel printer characterization and calibration.
机译:提出了一种方法,其中k-均值聚类技术被应用于将微尺度的单色半色调图像分割成三个部分:固体墨水,墨水/纸张混合区域和未打印的纸张。该方法已经通过基于振幅(AM)和频率调制(FM)技术半色调的基于冲击(偏移)和非冲击(电子照相)的单色打印进行了评估。印刷样品还包括纸基材的一系列变化。已在CIELAB颜色空间中对分段区域的颜色进行了分析,以揭示变化,尤其是混合区域中的变化。分割区域中强度分布的统计数据已被用于导出可用于计算简单阈值的表达式。然而,与使用Murray-Davies公式的传统估计技术相比,分割结果已被用于研究点增益。已经使用估计和测量的参数报告了通过光谱Murray-Davies模型预测半色调反射率的性能。最后,提出了一个一般的想法来扩展基于经验金属观测的经典Murray-Davies模型。因此,本研究主要介绍了针对色彩预测模型表征半色调印刷介质相互作用的实验成果。当前,大多数基于回归的颜色预测模型都依靠数学优化来使用与点大小相比大面积的平均反射率来估计参数。尽管这种通用方法已被接受为有用的工具,但实验研究可以增强对物理过程的理解,并有助于探索新的建模策略。此外,报告的发现可能有助于减少在多通道打印机表征和校准过程中需要打印和测量的样本数量。

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