A Cloud-Based Image Processing Framework for Precision Digital Color Management in Fashion Design

Digital Color Management (DCM) has become essential in precision driven design industries. This study proposes a cloud based image processing framework to enhance digital color consistency, accuracy, and production efficiency in fashion design. The proposed system integrates a novel multi stage color correction algorithm based on International Color Consortium (ICC) profile optimization, adaptive histogram equalization, and device independent color matching. Additionally, a synchronization module built on scalable cloud architecture enables real-time color data sharing across distributed design teams. Experimental evaluations demonstrate significant improvements in inter device color fidelity (average E reduction of 37%) and a 28% reduction in prototyping iterations. System latency was optimized through a lightweight data compression protocol, reducing average cloud sync delay to 120 ms. The framework also supports virtual prototyping, enabling sustainable design practices by minimizing physical sample waste. This research contributes to the field of computational design by delivering a robust, scalable, and sustainable DCM solution applicable to broader creative and industrial design ecosystems.