Research on large color difference evaluation using printed samples
A grey-scale psychophysical experiment was carried out for evaluating color differences using printed color patches. In total, 100 pairs of printed samples were prepared with an average ΔE*ab of 13.8 units. Each pair was assessed 60 times by a panel of 20 normal color vision observers. The visual results were used to test the existing color-difference formulae. The results showed that all formulae gave quite satisfactory performance except OSA-Ep-Gu, which is the formula for calculating the magnitude of small-medium color difference. The optimized kL values were used to compare with the medium color difference (MCD) of the earlier studies. The results showed that they agreed well with each other.
APPLICABILITY OF STANDARD GREY SCALE FOR REPORTING PERCEIVED COLOR DIFFERENCE OF PRINTS ENHANCED WITH PEARLESCENT PIGMENTS
Printed materials that exhibit goniochromism pose a challenge not only for colour measurement but also for estimating colour differences. A common procedure for determining perceived colour difference implies assessing colour pairs by means of a standard grey scale. This method was proven to be adequate for estimating, among others, perceived differences of low chroma goniochromatic samples found in the automotive industry, as well as for assessing colour differences of conventional prints. In this work, we were interested in the applicability of the same approach for estimating colour differences of printed samples enhanced with pearlescent pigments. Such prints are regarded as goniochromatic and depending on the type of the pigment, can exhibit very high chroma in angles close to specular reflection. This may pose a problem in evaluating colour differences because grey scale only shows a change in lightness. In addition, in some illumination/viewing geometries the differences between the two samples can be higher than those presented in the grey scale. Nine colour pairs (low-chroma digitally printed samples enhanced with three types of pearlescent pigments) were assessed in six viewing/illumination angles by a panel of ten observers. Our results show that chroma of the samples did not influence significantly interand intra-observer agreement, implying that grey scale references can be used for determining the perceived differences between chromatic samples. SDC grey scale provided sufficient range of colour differences only for the limited set of printed samples, leading to the conclusion that for assessing the differences of printed samples enhanced with pearlescent pigments it is necessary to use reference scale with higher difference range.
Color image based sorter for separating red and white wheat
A simple imaging system was developed to inspect and sort wheat samples and other grains at moderate feed-rates (30 kernels/s or 3.5 kg wheat/h). A single camera captured color images of three sides of each kernel by using mirrors, and the images were processed using a personal computer (PC). Real time image acquisition and processing was enabled on an ordinary PC under Windows XP operating system using the IEEE 1394 data transfer protocol, DirectX application software, and dual-core computer processor. Image acquisition and transfer to the PC required approximately 17 ms per kernel, and an additional 1.5 ms was required for image processing. After classification, the computer could output a signal from the parallel port to activate an air valve to divert (sort) kernels into a secondary container. Hard red and hard white wheat kernels were used in this study to test and demonstrate sorter capability. Simple image statistics and histograms were used as features. Discriminant analysis was performed with one, two, or three features to demonstrate classification improvements with increased numbers of features. The sorter was able to separate hard red kernels from hard white kernels with 95 to 99% accuracy, depending on the wheat varieties, feed-rate, and number of classification features. The system is an economical and useful instrument for sorting wheat and other grains with high accuracy.