Color Balance & Calibration
The Challenge: Ensuring color accuracy and consistency is difficult to balance across multiple corrected images, especially when one mistake can lead to an unhappy customer.
The Solution: An automated AI model that compares and evaluates colors against provided HEX codes and references, flagging issues so inconsistencies can be easily addressed.
In e-commerce, we often have a series of images of the same item. Maybe a jacket, seen spread out in one image, on a model in the next, and a closeup detail shot to wrap it up. But sometimes, after post-production, or because of issues on set, the colors end up slightly different from the original colors watch, or even different between the images. Even if it’s only ever so slightly, it still throws off the buyer and makes the brand look less professional.
As part of our effort to help our customers with quality control, we are developing AI models to find the object in all the images and compare the colors, not just to each other, but also to a provided HEX code or color reference.
First, we make sure to find the actual item, the jacket in this case, in all the photos. Once identified, we segment or isolate the object. Then, it is time to use our adaptive color lookup to check the actual color, even if it's in shadow or harsh light.
When there is a discrepancy, our system flags this for further decision-making in the QC stage.
Once such an issue is found, we will first alert the user responsible for quality control that something needs to be looked into. Next, we might suggest using our Color Change AI to dial the color to the correct hue and saturation.
So imagine always catching and correcting any color balancing issues on any product image. We’re here for you to make that happen.