仪器颜色合格/不合格分析的进展

S. Westland, Q. Pan
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引用次数: 1

摘要

对于大多数纺织品生产公司来说,能够对两个样品的视觉颜色是否匹配做出可靠的决定是一个重要的商业考虑因素[1,2]。传统的视觉合格/不合格分析是由训练有素的色彩师进行的。然而,这些视觉决策受到许多问题的影响,这些问题会使它们变得不可靠。大约8%的男性人口有色觉缺陷(俗称色盲),这意味着成对的样本可能与他们的视觉匹配,尽管看起来与其他所谓的正常观察者非常不同[3]。在正常观察者中也发现了一些色彩视觉的变化[4],并且观看环境的影响可以影响视觉决策。尽管使用高质量的观察柜可以减少通过/不通过决策的变化,但观察对样本的橱柜中背景的颜色也会极大地影响视觉差异的大小(“脆化”效应)[5]。1953年,8名训练有素的色彩师对287对样品进行了视觉评估[6],后来对这些数据的分析表明,24.5%的应该通过的对被拒绝,13.3%的应该被拒绝的对通过了[1]。此后进行了几项这样的研究,人们普遍认为,在做出视觉合格/不合格决定时,多达25%的“错误决定”是由专业色彩师做出的[7]。这种通过/不通过决定的可变性可能是昂贵的,仪器方法已经使用了至少50年。本文考虑了仪器色差评估的现状,并强调了一些最佳实践。
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Advances in Instrumental Colour Pass/Fail Analysis
The requirement to be able to make a reliable decision about whether two samples are a visual colour match is an important commercial consideration for most textile production companies [1,2]. Traditionally visual pass/fail analysis was carried out by trained colourists. However, these visual decisions are subject to a number of problems which can make them unreliable. Approximately 8% of the male population have a colour vision deficiency (known colloquially as colour blindness) which means that pairs of samples may be a visual match to them despite appearing to be very different to other so-called normal observers [3]. Some variation in colour vision also is found in normal observers [4] and the effect of the viewing environment can affect visual decisions. Although the use of high-quality viewing cabinets can reduce variation in pass/fail decisions even the colour of the background in the cabinet against which the pair of samples are viewed can greatly affect the magnitude of the visual difference (the ‘crispening’ effect) [5]. In 1953 an analysis of 287 pairs of samples were visually assessed by 8 trained colourists [6] and a later analysis of these data showed that 24.5% of the pairs that should pass were rejected and 13.3% of the pairs that should be rejected were passed [1]. Several such studies have since been carried out and it is widely understood that as many as 25% ‘wrong decisions’ are made by professional colourists when making visual pass/ fail decisions [7]. This variability in the pass/fail decision is potentially costly and instrumental methods have been available for at least 50 years. This paper considers the current state of instrumental colourdifference evaluation and highlights some best practice.
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