Abstract: As the center of the overall visual effect of a suit, the suit collar is the most crucial factor that affects the overall visual impression. In creating clothing patterns based on design sketches, the judgment of important detailed dimensions like the suit collar often relies on the experience of pattern makers and their repeated trials and errors. Therefore, using computer vision to assist in determining the detailed dimensions of the suit collar is of great significance. However, current research on clothing measurement mainly focuses on measuring the outer contour dimensions, with unsatisfactory results for measuring the internal contour dimensions.
Low contrast in the internal contour lines of clothing makes it difficult to extract feature points and complete contours and further results in the difficulty of measuring internal dimensions from images. To address this issue, a method based on the SAM model for segmenting components to extract internal dimensions was proposed. Firstly, the SAM model was used to segment the suit collar components to improve the edge accuracy. Next, the DP algorithm was used to approximate the suit collar components into polygons, and the LSD algorithm and geometric constraints were employed to correct the errors generated during the polygon approximation process. Finally, a structural model of the suit collar was established by incorporating pixel ratios to extract relevant data.
Three main conclusions are drawn. First, by segmenting the suit collar components with the SAM model, the masks of lapel, reverse collar and collar stand were obtained. Second, by using the LSD algorithm and geometric constraints to adjust the suit collar component polygon result, a suit collar structural parameter model through linear and parabolic functions was constructed. Third, the main design dimensions of the suit collar were measured, and the results showed that compared with the measurement software, the absolute error of dimensions ranged from 0.02 cm to 0.74 cm, and the absolute error of angles ranged from 0.02 to 0.27 . Compared with the physical measurement, the absolute error of dimensions ranged from 0.05 cm to 1 cm, and the absolute error of angles ranged from 0.06to 0.68. The measurement error met the standards for clothing measurement.
This method can provide pattern makers with reference dimensions for the suit collar, enhancing the efficiency of transitioning from design to sample. The dimensions obtained in this study are plan view sizes and not the actual dimensions of the clothing sample. In future studies, the mapping relationship between the two will be further explored to make corrections and adjustments.

Key words: suit collar, garment parts' segmentation, SAM model, LSD algorithm, style drawing extraction, size measurement 

摘要： 针对服装内部轮廓线对比度低、提取特征点和完整轮廓困难，导致图像内部尺寸难以测量的问题，提出一种基于SAM模型进行部件分割提取内部尺寸的方法。首先通过SAM模型分割西装领部件，然后将西装领部件近似多边形并利用LSD算法修正多边形，最后建立西装领结构模型并结合像素比例提取设计尺寸。结果表明：该方法可以从成衣图像中提取西装领款式结构图并输出相关数据，实验测量结果与测量软件相比尺寸的绝对误差在0.02~0.74 cm之间，角度的绝对误差在0.02~0.27之间；与实物测量相比，尺寸的绝对误差在0.05~1 cm之间，角度的绝对误差在0.06~0.68之间。该方法提取的西装领细部尺寸可为制版师提供数据参考。

关键词: 西装领, 服装部件分割, SAM模型, LSD算法, 款式图提取, 尺寸测量