Perception

Color Histogram

A color histogram is a representation of the distribution of colors in an image or region, counting pixel frequencies across bins of a color space such as RGB or HSV. Histograms are invariant to translation and rotation and robust to partial occlusion, which made them a staple of classical object recognition, image retrieval, and tracking methods such as mean-shift and CAMShift. They discard all spatial structure, limiting discriminative power compared to learned features.

Why it matters for physical AI

Though superseded by deep features for recognition, color statistics remain useful for lightweight tracking, dataset curation, and detecting domain shift between training and deployment imagery in robot vision pipelines.