Color is a critical aspect of product design and quality control across many industries. Precisely measuring color differences allows designers and manufacturers to ensure consistency and accuracy. The CIE L*A*B* (also referred to as CIELAB or Lab) color space is a widely used model for objectively quantifying color. Within this system, Delta E (ΔE) represents overall color difference between two samples. Understanding Delta E provides key insights into perceivable color shifts and is fundamental for color quality control.
Overview of the CIELAB Color Space
Developed in 1976 by the International Commission on Illumination (CIE), the CIELAB color space aims to create a standardized quantitative model for color perception. Unlike the RGB and CMYK color models which relate to device specific color mixing, CIELAB is device independent and based on human visual interpretation.
The three dimensions of the CIELAB model are:
- L* – Lightness from 0 (black) to 100 (white)
- A* – Green/Red color axis (-a = green, +a = red)
- B* – Blue/Yellow color axis (-b = blue, +b = yellow)
The a* and b* axes have no specific numerical limits. Together, the L*, a* and b* values precisely define a color in a device independent manner that matches human perception.
Understanding Delta E
Delta E (ΔE) represents the total difference between two colors within the CIELAB color space. It is a single numeric value that combines the differences between the L*, a* and b* coordinates of the two colors being compared.
The Delta E between two colors is calculated using the following equation:
Where:
- ΔL* – Difference in lightness between the two colors
- Δa* – Difference in green/red value
- Δb* – Difference in blue/yellow value
The resulting ΔE provides a quantitative measure of the perceived color difference. A higher ΔE indicates greater separation between two colors, while a lower ΔE indicates the colors are more similar.
CIELAB Color Difference – Table
| ΔE | Perceived Color Difference |
|---|---|
| ΔE ≤ 1 | Not perceptible by human eyes |
| 1 | Perceptible through close observation |
| 2 | Perceptible at a glance |
| 10 | Colors are more similar than opposite |
| ΔE > 50 | Clearly noticeable difference |
While ΔE values higher than 1 indicate a visible difference, acceptable thresholds vary across industries. For example, a ΔE of 2 to 3 may be acceptable for house paints, while textile manufacturers may aim for ΔE under 1.
Significance of Delta E in Color Quality Control
Delta E provides a standardized metric for color variation which is vital for quality control across many fields including:
- Textiles – Ensures dye lots and finished fabrics match specifications
- Plastics & Coatings – Verifies consistency across production runs and facilities
- Printing – Validates printer calibration and repeatability
- Automotive Paint – Confirms color uniformity within and between vehicle models
- Food & Beverage – Checks match to established color standards for products
By using ΔE values rather than relying solely on human visual assessments, manufacturers can objectively pass or fail samples against color quality thresholds. This reduces subjective errors and disputes.
Delta E is commonly used for color quality control via the following workflows:
Batch Approval
In this application, a color measurement device is used to obtain L*a*b* values for a sample from a newly created batch. The ΔE is calculated between this and the defined standard for that color. If the ΔE falls within the acceptable range, then the batch is approved. When ΔE exceeds the threshold, the production parameters must be adjusted to achieve a closer color match.
Production Monitoring
Here ΔE serves as a metric for ongoing quality auditing during a production run. Periodic color measurements are taken and ΔE is tracked over time. This allows operations managers to identify color drifts and intervene before batches are out of specification.
Failure Diagnosis
When a color failure occurs, the diagnostic power of ΔE can help identify the root cause. By calculating ΔE values between the failed sample and targets at different production stages, the step at which the color deviation occurred can be isolated.
Using Delta E in Product Design
The ability to numerically compare color differences makes Delta E useful during product development as well:
- Evaluate minimum perceivable shifts between colors during design of patterns and logos
- Specify tolerance limits for custom colors
- Determine when reformulation is needed to match a physical sample
- Assess visual impact when substituting alternate materials
Detailed ΔE data aids designers in decision making to achieve aesthetically pleasing, yet manufacturable products.
Delta E Calculation Considerations
While an invaluable tool, proper use of Delta E requires understanding key considerations:
- Formula – The simplest Euclidean ΔE calculation has limitations. More complex formulas like CIE94 and CIEDE2000 improve perceptual uniformity.
- Color Space – Delta E may be computed between colors defined in spaces other than CIELAB including XYZ, sRGB and more.
- Instrumentation – Measurement device, geometry, calibration, etc. affect accuracy. Stick to one standardized setup.
- Samples – Surface properties, gloss, texture impact readings. Use consistent representative specimens.
- Illumination – The reference light source should match measurement and viewing conditions.
Consulting metrology experts helps establish proper ΔE methodology for a given application.
Conclusion
Delta E provides an objective numeric assessment of color difference within the widely used CIELAB color space. It enables manufacturers to reliably control color quality against established tolerances and also aids product designers in color selection decisions. However, utilizing Delta E requires methodology suited to the specific application and samples involved. When applied properly, Delta E delivers actionable data for process improvement and ensures perceived color matches human vision.
