A Study on the stylized generation of cross-generational multi-kiln teaware driven by interactive genetic algorithms

Teaware, as a pivotal carrier of ceramic cultural heritage, encapsulates the craftsmanship, ingenuity, and aesthetic culture of specific historical epochs. However, digital inheritance of ancient kiln teaware lacks parametric deconstruction of intrinsic kiln styles and controllable generation for cross-kiln integration. This study proposes an interactive genetic algorithm framework that constructs a sample database of eight representative kilns (Tang-Qing), deconstructs styles into shape, glaze, and decoration parameters, establishes parametric generation for flexible control and efficient rendering of forms and visual features, and builds a three-layer genetic coding system to map cultural traits into digital genes, thereby producing style-controllable digital twins. This research offers a novel approach for the digital reproduction and dissemination of ceramic cultural heritage.