Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 69 | Paint Color and Gloss Classification Device |
James Lee Victoria Lee |
Chihun Song | design_document1.pdf proposal1.pdf |
|
| # Title Paint / Sheen Analysis Device # Team Members: - James Lee (jl212) - Victoria Lee (vlee33) # Problem Homeowners, renters, and especially college students frequently face the challenge of matching existing wall paint and texture for touch up or repairs often without access to the original paint can. While it is possible to peel a physical chip off the wall to scan it, it is an inconvenient process. While mobile apps exist they rely on smartphone cameras which use auto white balance and are heavily infused by ambient lighting. These current solutions do not account for sheen such as matte vs eggshell meaning that even the best color match can look off once applied. This resulted in wasted time and materials and a poor result / color match. # Solution We propose a non-destructive "Paint/Surface Analysis Device" that accurately identifies both wall color and sheen without removing a physical paint chip. Our device utilizes a controlled lighting environment and a spectral color sensor to determine the precise color composition (hex code) of the wall. To address the gloss, the device integrates a secondary computer vision subsystem utilizing "raking light" (low-angle side lighting). This illumination technique reveals the paint finish (e.g., gloss vs. semi-gloss) Describe your design at a high-level, how it solves the problem, and introduce the subsystems of your project. ## Subsystem 1: Microcontroller and Processing Coordinates sensor data acquisition, executes matching algorithms, and manages system timing. It converts spectral data into the standard color space. From there, we match the color to color database stored in memory. Components: STM32F7 Series Microcontroller (High-performance with DCMI for camera support) ## Subsystem 2: Sheen Analysis We intend to shine an LED light at a 60 degree angle and measure how much light bounces off. If there is a lot of bounce the surface would be considered glossy if there is little bounce the surface would be considered matte. Components: Low-angle "Raking Light" LED array, AS7341 11-Channel Spectral Sensor, calibrated neutral-white LED, Photodiode ## Subsystem 3: Spectral Sensing Measures the absolute color composition of the sample under calibrated internal lighting. Components: AS7341 11-Channel Spectral Sensor, calibrated neutral-white LED ## Subsystem 4: User Interface Displays the identified paint brand, color name, and recommended applicator type. Components: 2.8" TFT LCD Display, Rotary Encoder for menu navigation ## Subsystem 5: Power Management Regulates external power for sensitive analog sensors and high-current LED subsystems. Components: 12V DC Wall Adapter, Buck Converters (5V), and Low-Noise LDO Regulators (3.3V) ## Subsystem 6: Enclosure Blocks outside light and fixes spectral sensor position/angle for reproducible results Components: Cardboard Box with fixed cutouts for reproducible measurements # Criterion for Success Color Accuracy: Achieve a color match with a Delta-E < 3.0 across multiple measurements, which represents a commercially acceptable match for consumer-grade applications. How Is Color Measured? Calculating Delta E | ALPOLIC® Sheen Classification: Correctly distinguish between "Gloss," "Semi-Gloss," and “Flat” with 90% accuracy. Ambient Isolation: Maintain consistent color readings regardless of external room lighting conditions. |
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