# Image-Processing-Driven Modeling and Reconstruction of Traditional Patterns via Dual-Channel Detection and B-Spline Analysis

## TL;DR

This paper introduces a new method for digitally analyzing and reconstructing traditional patterns using image processing and B-spline modeling.

## Contribution

The novelty lies in combining dual-channel image processing with parametric modeling and topological reconstruction for traditional pattern analysis.

## Key findings

- A dual-channel image processing algorithm successfully extracts and vectorizes graphic primitives from traditional patterns.
- B-spline curves enable parametric control and structural integration of the extracted primitives.
- Fractal dimension analysis quantifies pattern complexity, aiding in cultural heritage imaging applications.

## Abstract

This study aims to address the research gap in the digital analysis of traditional patterns by proposing an image-processing-driven parametric modeling method that combines graphic primitive function modeling with topological reconstruction. The image is processed using a dual-channel image processing algorithm (Canny edge detection and grayscale mapping) to extract and vectorize graphic primitives. These primitives are uniformly represented using B-spline curves, with variations generated through parametric control. A topological reconstruction approach is introduced, incorporating mapped geometric parameters, topological combination rules, and geometric adjustments to output topological configurations. The generated patterns are evaluated using fractal dimension analysis for complexity quantification and applied in cultural heritage imaging practice. The proposed image processing pipeline enables flexible parametric control and continuous structural integration of the graphic primitives and demonstrates high reproducibility and expandability. This study establishes a novel computational framework for traditional patterns, offering a replicable technical pathway that integrates image processing, parametric modeling, and topological reconstruction for digital expression, stylistic innovation, and heritage conservation.