Automatic machine embroidery image color analysis system, part II: Application of the genetic algorithm in search of a repetitive pattern image

Abstract

This series of studies proposed an automatic machine embroidery image color analysis system. Based on the machine embroidery image color separation system proposed in part I of this series of papers (Kuo CFJ, Jian BJ and Wu HC. Automatic machine embroidery image color analysis system, part I: using Gustafson-Kessel clustering algorithm in embroidery fabric color separation. Textil Res J 2011, submitted for publication), this paper presents an automatic repetitive pattern image recognition algorithm for machine embroidery. Firstly, the image pre-processing is implemented to eliminate image acquisition noise and smooth the texture of machine embroidery. After the completion of image pre-processing, the genetic algorithm (GA) is applied to obtain the color image of repetitive patterns. The novel fitness function proposed in this paper can increase the calculation of the color entropy value to improve the measurement block accuracy of color similarity in previous literature. When applied to the GA, the system can accurately identify and cut out images of repetitive patterns. In addition, since the proposed fitness function has been normalized, it can accurately calculate the optimal target function, indicating that the proposed algorithm can automatically and accurately identify and cut out the images of repetitive patterns in machine embroidery.