标题: | 以亮度/色彩对比为基础的影像分析技术之研究 A Study of Image Analysis Techniques Based on Luminance/Color Contrast |
作者: | 陈信嘉 Hsin-Chia Chen 王圣智 Sheng-Jyh Wang 电子研究所 |
关键字: | 云彩;彩色切割;色彩对比;可见色差;Mura;Color Segmentation;Color Contrast;Visible Color Difference |
公开日期: | 2006 |
摘要: | 在本论文中,我们提出以亮度/色彩对比为基础的客观视觉评量以估测人类主观视觉感受评量。针对不同的影像分析应用,如自动面板缺陷检测应用及彩色切割应用,我们先透过设计视觉实验得到人类在分析影像时的主观视觉评量标准,并设计客观评量因子来估测这些主观视觉评量,最后再将这些客观评量因子应用在自动面板缺陷检测、彩色切割评量技术以及彩色切割技术上。 在传统的影像分析系统流程中,包含有四个基本的步骤: 1) 影像撷取,2) 影像分析,3) 输出影像分析结果,及 4) 分析结果评估。具体而言,在一个影像分析系统中,在输入端我们输入一张或多张影像进行分析,此系统将针对不同的影像分析应用,使用不同的影像分析技术来分析影像,并输出分析结果。然后,再根据一些视觉感受评量来对影像分析结果进行评估。在这篇论文中,我们在传统的影像分析系统流程中,增加两个重要的分析程序,分别是视觉实验以及亮度/色彩对比测量。为了得到和人眼主观视觉分析影像一致之结果,我们针对不同的影像分析应用,分析亮度/色彩对比在人眼视觉感知中所扮演的角色。透过视觉实验,我们针对不同的影像分析应用,定义合适的亮度/色彩对比,并且粹取出符合人类视觉感受的主观视觉评量因子。之后,为了量测这些主观视觉评量因子,我们以亮度/色彩对比为基础来发展客观的视觉评量因子估测方法,并且应用在发展影像分析技术,以此来得到和以人眼分析影像近似的方法和结果。 对于不同的影像分析应用,人眼的主观视觉评量因子可能不尽相同。在这篇论文中,我们讨论了两种不同的影像分析应用:1) 自动面板缺陷检测以及2) 彩色切割应用。在自动面板缺陷检测的应用中,我们讨论人类主观视觉对低亮度对比的面板缺陷影像的之视觉评量因子及其量测问题。首先,我们先介绍在Mori 等人发表的论文中所提到的以亮度对比为基础的主观视觉因子及其量测公式□ SEMU 公式,同时介绍他们得到此一视觉因子的视觉实验。结合SEMU 公式,我们提出了一些影像分析技术,试着来侦测不同形态的面板缺陷。其中包括我们提出合适的侦测运算子,如 LOG 运算子,并且讨论最佳的自动门槛值设定方法。 在彩色切割应用方面,我们针对包含少量纹理的彩色切割应用,考虑了人眼对于色彩对比的感受。在一张包含少量纹理的彩色影像中,低色彩对比的相邻像素往往被视为相同的影像区块,而相邻高色彩对比的像素位置则为影像区块的边界。因此,我们在论文中讨论人眼对色彩对比和色差的感受评量。另外,针对彩色切割应用,我们也考虑了人眼对于色彩对比的主观视觉评量因子,如人眼对于过度切割 (over-segmentation) 的程度感受以及不足切割 (under-segmentation) 的程度感受 … 等等。对此,在论文中,我们透过视觉实验来验证这些主观的视觉评量因子和彩色切割结果品质的关系。之后,我们设计了一些以色彩对比为基础的客观视觉评量方法,来估测这些主观视觉评量因子。同时,我们结合这些设计出来的客观视觉评量量化估测方法,应用在客观的彩色切割结果评量以及发展彩色切割演算法的应用上。 最后,我们模拟验证了所提出的以亮度/色彩对比为基础的影像分析技术在不同的应用上的分析结果。其结果验证,我们以亮度/色彩对比为基础所设计的客观评量因子和人类的主观视觉评量因子有很高关联性。而且,我们也验证了,在针对不同的影像分析应用所设计的影像分析技术中,亮度/色彩对比的确扮演着不可或缺的角色。因此,如果可以有效率且有效地估测亮度/色彩对比,并且用亮度/色彩对比为基础来发展客观视觉评量,以估测人眼在不同影像分析应用中的主观视觉评量因子,我们可设计得到近似人类分析影像方法及结果的影像分析技术。 In this dissertation, a study of image analysis techniques by correlating subjective visual qualities with objective visual quantities based on luminance/color contrast is presented. To mimic the way humans perform image analysis, some subjective visual quantities are considered. To extract and verify the applicability of these visual quantities, subjective experiments are performed first. Then, to measure these subjective visual quantities, some objective quantitative measures based on luminance/color contrast are proposed. With these objective quantitative measures, contrast-based image analysis techniques can be developed for various image analysis applications. In the flow chart of a conventional image analysis system, four basic parts are included: 1) inputting of images to be analyzed, 2) image analysis with one or more techniques, 3) outputting of analyzed results, and 4) evaluation of the analyzed results. Specifically, given one or more images to be analyzed, different image analysis techniques are adopted for different applications. Then, the analyzed results are evaluated with some evaluation methods according to predefined visual perception requirements. In this dissertation, two more processes are added into an image analysis system. They are 1) subjective experiments and 2) measurement of luminance/color contrast and/or measurement of visual perception quantities. To mimic the way humans perform image analysis, we need some suitable subjective visual quantities. To extract appropriate visual quantities that may well correspond to humans’ perception, subjective experiments are needed. To estimate these subjective visual quantities for different applications, we need to propose effective and efficient objective quantitative measures. In this dissertation, we consider two different image analysis applications: 1) automatic inspection for visual defects on LCD panels, and 2) color segmentation. For different image analysis applications, the applicable visual quantities will be different. In the automatic defect inspection application, we discuss the suitable visual quantities for the extraction of visual defects with low luminance contrast. Here, we follow Mori’s proposal to quantify the degrees of image defects based on the luminance contrast and area size of visual defects. Based on Mori’s subjective experiments, which were performed to relate human visual perception with the luminance contrast and area size of visual defects, and the SEMU formula, which was proposed by Mori et al for a quantitative measurement of visual perception, we may effectively quantify the degrees of image defects based on luminance contrast and defect area. The LOG operator is then used to detect several types of visual defects. An optimal thresholding mechanism is also discussed. For the applications of color segmentation with little texture, we consider segmentation quality, degree of over-segmentation, and degree of under-segmentation as the visual quantities. To verify the correlation among these visual quantities, a few subjective experiments are performed. Here, we use color contrast to quantify these visual quantities. Usually, given a color image, adjacent pixels with low color-contrast are grouped into regions; while adjacent pixels with high color-contrast are regarded as edges. For color segmentation, we define color-contrast in terms of visible color difference and invisible color difference. Then, some objective quantitative measures based on visible/invisible color difference are proposed to measure these aforementioned subjective visual quantities. In this dissertation, the “intra-region visual error” is proposed to measure the degree of under-segmentation, while the “inter-region visual error” is proposed to measure the degree of over-segmentation. With these visual measures, some image analysis techniques are proposed to perform color segmentation and also the evaluation of color segmentation. With simulations for these two image analysis applications, some conclusions are drawn. First, the correlations between the luminance/color contrast-based quantitative measures and the visual quantities are really significant. Second, luminance/color contrast may play an important role in the development of image analysis techniques that mimic the way of human perception. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT008811590 http://hdl.handle.net/11536/53223 |
显示于类别: | Thesis |
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