在指纹识别技术应用范围内，指纹纹线密度作为指纹形态学特征之一，其研究价值日益凸显。针对现有测量方法存在的耗时、工作量大等问题，提出一种基于算法的自动化测量方法。该算法首先对指纹图像进行预处理，包括灰度化、边缘检测、降噪和纹线增强，以提高图像质量和清晰度；然后，通过强化指纹特征，数组转换、确定方向向量、峰值检测、最后绘制灰度值波动图，直观展示测量结果。实验结果表明：自动测量算法在效率和准确性上较好，同人工测量结果之间具有较高的一致性和显著的统计相关性，进一步证实了自动测量方法的科学性和有效性，为指纹识别的自动化和智能化提供了新的思路和方法。

In the field of fingerprint recognition technology, ridge density, as one of the morphological features of fingerprints, has demonstrated increasing research value. Aiming at the problems of time-consuming and labor-intensive existing measurement methods, an algorithm based automated measurement method was proposed. The algorithm first preprocessed fingerprint images, including grayscale conversion, edge detection, noise reduction, and ridge enhancement, to improve image quality and clarity. Subsequently, it strengthened fingerprint features, performed array transformation, determined directional vectors, detects peaks, and finally plotted a grayscale fluctuation diagram to visually present the measurement results. Experimental results show that the automated measurement algorithm performs well in terms of efficiency and accuracy, exhibiting high consistency and significant statistical correlation with manual measurements. This further validates the scientific robustness and effectiveness of the automated measurement method, providing new perspectives and approaches for the automation and intelligence of fingerprint recognition.