Specific locations of color shifts and uneven coloring can be identified instantly
Color management through quantification of colors is possible!!
Weaknesses and issues of traditional color management have been resolved! We present a new color management method!
Issues with Traditional “Color” Management Methods
Weaknesses of Color Management Using Traditional Spectroscopic Methods
1. The range of measurement is narrow
2. With only numerical data, it is difficult to imagine what the colors are actually like
1. Even when photographing color samples that are standard for traditional cameras, the colors are captured slightly differently from how they are seen
2. The color samples themselves become discolored as time passes
3. The colors seen are sensed differently by each person
Depart from the Traditional Visual Inspections Using Boundary Samples
1. It is possible to identify subtle differences in color
2. Colors for three-dimensional objects can also be measured
3. By overlaying images of a standard object (approved object) and an object to be inspected, measurements and specialties of color differences are displayed for each region (color comparison and management are possible for the entire pattern without color patches)
4. Image data can be saved
→Contributes to accumulation of color data and realization of traceability
→Through data sharing, reduces personal error, which is inevitable for visual inspections, and trouble with client criteria
Differences in the Range of Measurement Compared to Traditional Colorimeters
The yellow frame in the figure to the left is the range of measurement for 2D colorimeters
The blue frame is the range of measurement for traditional spectrophotometers
Because traditional spectrophotometers use a point as their range of measurement, only solid colors can be measured. However, because 2D colorimeters measure a plane, measurement over a wide range allows measurement of lamé, metallicity, and patterns.
The average Lab value differential is derived by subtracting the average Lab value of the standard image from the average Lab value of the image to be inspected.
The CMYK ratio is the CMYK ratio of the image to be inspected when the standard image is set as 100%.
The CMYK value serves as a guide for the control direction of dot gain for the image to be inspected.
Positive values → Increase the dot gain density
Negative values → Decrease the dot gain density
*The Display of Average Lab Value Differential/Average⊿E and CMYK Ratio Can Be Toggled with a Button
Further details can be inspected multilaterally based on saved images
RCView and RCSence, color analysis software specific for 2D colorimeters, can be used
S123, XYZ, xy, Lab, RGB, CMY CMYK, color distribution coincidence, etc…
・2D Colorimeter RC-500
・High color rendering fluorescent lamp
|Valid Pixels||Roughly 5 million pixels
|Valid Area||8.47(h) ×7.10(v) mm|
|Shutter Speed||1/1000sec -1sec|
|Image Import Time||Less than 2 seconds|
|Lens Mount||F Mount|
|Main Body Size||W100×D130×H100 (mm)|
|Monitor||EIZO Brand ColorEdge Series|
|Measurement PC||Memory8GB Windows7 Compatible|
During Operation: 10 - 35 °C
Outside of Operation: -10 - 50 °C
During Operation: 20 - 80% (No condensation)
Outside of Operation: 20 - 80% (No condensation)
Color Management Through ⊿E and Color Distribution Coincidence
2 specified images photographed by the 2D colorimeter are analyzed using specific software, and the average ⊿E and color distribution coincidence are calculated from color data containing several million pixels.
・The ⊿E values represent color difference. Within the specified range of measurement, the Lab values for the standard object and the object to be inspected are used to derive the average ⊿E.
・The color distribution coincidence represents the degree of overlap of the volume of the 2 chromaticity distributions as a percentage, when the chromaticity distributions of the standard object and the object to be inspected are overlaid on an xy chromaticity diagram. Because chromaticity distributions contain texture information, in addition to color information, the coincidence values reflect 2 types of information: color differences (hue and saturation) and texture differences (shape of the chromaticity distribution).
By quantifying color differences and texture differences through the average ⊿E and coincidence values, personal error issues, which is inevitable for visual inspections, and trouble with client criteria can be reduced, enabling standardization of colors and balanced color management.
Overlay images A and B and display the color distribution coincidence and average ⊿E
Segment the image vertically and horizontally, and measure coincidence and average ⊿E for each block. Measurement results for coincidence are noted as a numerical value (%), and decreases in this value indicate greater differences in color between the measurement object and the standard object. Also, as the average Lab value differential, average ⊿E, and CMYK ratio are displayed, they serve as guides for color adjustment.
About the Range of Measurement
The range of measurement can be specified based on the object and location to be measured, such as measurement of each block, measurement of several specified ranges, and measurement of the entire image.
*What Are the L, a, b, and E Displayed in the Range of Measurement?
They are ⊿L, ⊿a, ⊿b, and ⊿E and represent differences between the standard object and the object to be inspected
What is Color Distribution Coincidence?
1. Take the chromaticity distribution within the same region.
Chromaticity distribution is two dimensional statistical data built by stacking up xy chromaticity coordinates for each pixel in the measured image region.
2. The degree of overlap of the volume of the chromaticity distribution statistical data is calculated as the color distribution coincidence.
This value represents the degree of overlap with 100% (complete coincidence) as the maximum. This is color distribution coincidence.