Color Difference Detection

Utilizing high-resolution industrial color cameras, multispectral cameras, color sensors, or spectrophotometers, combined with high Color Rendering Index (CRI) standard lighting and color correction algorithms, this solution establishes a high-precision automated color detection system. The system objectively measures the hue, chroma, and lightness of product surfaces, effectively eliminating color judgment errors caused by ambient lighting, manual interpretation, and operator experience.

Through high-speed image analysis and color comparison technology, the system can identify subtle color deviations between products in real time. It is widely applied in processes such as plastic injection molding, coating, printing, electronic products, food packaging, medical devices, and consumer products, ensuring color consistency and brand quality standards.

Standard Light Source Illumination

Employing a high Color Rendering Index (CRI) standard lighting system to provide uniform and stable spectral energy, reducing color errors caused by ambient light, shadows, and reflections, and establishing a consistent and repeatable measurement environment.

Multispectral Image Capture

Compared to conventional color cameras that capture only RGB three-channel data, multispectral cameras acquire information across multiple narrow spectral bands, obtaining more complete reflectance spectral data of the object. This effectively detects "metamerism"—cases where two objects appear similar in color under a specific light source but differ in spectral composition—enhancing the accuracy and stability of color difference detection. This makes it suitable for industries with extremely high color consistency requirements, such as coating, cosmetic packaging materials, and high-end consumer products.

Color Calibration and Color Space Conversion

Using a standard color chart to establish a camera color calibration model, converting RGB (or multispectral) image data into an internationally standardized color space (such as CIE Lab* ), ensuring measurement results align with human visual perception characteristics and maintain consistency across devices.

Color Difference Analysis

Comparing the measurement results with a master sample and calculating the color difference value ΔE based on CIE color difference formulas (such as CIEDE2000), while simultaneously analyzing the offset of each L* , a* , and b* axis to precisely determine the direction and degree of color variation.

Quality Judgment and Grading