Rice Cooker Shell Color Difference Recognition Dataset

The current industrial sector faces significant challenges in maintaining consistent product quality, particularly in color matching for manufactured goods. Existing solutions often fall short due to manual inspection limitations and subjective assessments, leading to undetected color discrepancies that affect customer satisfaction and brand integrity. This dataset aims to address the need for an automated system capable of detecting color differences in rice cooker shells, facilitating more reliable quality assurance processes. The dataset comprises images captured in a controlled environment using high-resolution cameras, ensuring clarity and detail. Data collection was performed in a lighting-consistent setting to minimize external variations. Quality control measures included multi-round annotations by trained inspectors and consistency checks to enhance reliability. Images are organized in a structured format for easy access and processing, stored in JPG format to balance quality and size.