Automatic measurement of traditional Chinese costume from its silhouette through Fuzzy c-means clustering method

Jiaqin Zhang,Jingan Wang,Le Xing,Hui’E Liang

doi:10.1177/1558925020978323

Abstract

As the precious cultural heritage of the Chinese nation, traditional costumes are in urgent need of scientific research and protection. In particular, there are scanty studies on costume silhouettes, due to the reasons of the need for cultural relic protection, and the strong subjectivity of manual measurement, which limit the accuracy of quantitative research. This paper presents an automatic measurement method for traditional Chinese costume dimensions based on fuzzy C-means clustering and silhouette feature point location. The method is consisted of six steps: (1) costume image acquisition; (2) costume image preprocessing; (3) color space transformation; (4) object clustering segmentation; (5) costume silhouette feature point location; and (6) costume measurement. First, the relative total variation model was used to obtain the environmental robustness and costume color adaptability. Second, the FCM clustering algorithm was used to implement image segmentation to extract the outer silhouette of the costume. Finally, automatic measurement of costume silhouette was achieved by locating its feature points. The experimental results demonstrated that the proposed method could effectively segment the outer silhouette of a costume image and locate the feature points of the silhouette. The measurement accuracy could meet the requirements of industrial application, thus providing the dual value of costume culture research and industrial application.

Highlights

In recent years, with the continuous awareness in preserving intangible cultural heritage, the protection and inheritance of traditional costumes have gradually become a research focus
The costume image segmentation results obtained from the images not preprocessed by the relative total variation model were poor, and the disadvantages were mainly due to: (1) texture changes near the edges of the costume silhouettes, which lead to the segmentation result without preprocessing being fuzzier; (2) the local texture of the costume without smoothing was recognized as the background; and (3) when the main color of the costume was close to the background, the costume target without smoothing of the local texture was less distinguishable from the background and was more difficult to segment
It was known that the relative total variation preprocessing algorithm proposed in this paper could effectively improve the segmentation effect of costume silhouettes, which was of great significance

Summary

Introduction

With the continuous awareness in preserving intangible cultural heritage, the protection and inheritance of traditional costumes have gradually become a research focus. Relative total variation image texture processing and the FCM clustering algorithm were used to intelligently extract costume silhouettes with complex textures. By using costume structure-based positioning of costume feature points, the automatic collection of traditional A-line costume dimensions was achieved.

Results

Conclusion