摘要 人脸检测作为识别技术的关键预处理环节，其准确性易受复杂环境的影响。针对传统Viola-Jones算法，提出一种基于MATLAB的可交互式改进界面。通过Haar特征模板提取面部多层次结构特征，结合级联分类器实现快速区域筛选；设计自适应阈值调整机制，允许用户通过Graphical User Interface界面自主调节五官的检测敏感度；最后集成检测系统，支持多部位独立检测与结果可视化。实验采用ORL与WIDER FACE数据库进行验证，结果表明在单人正脸场景下，面部检测率达100%，眼部、鼻部、嘴部分别为92.5%、97.5%和95%；多人场景下面部检测率为96.36%，较固定阈值模式提升12.7%。综合性能接近MTCNN模型，同时显存占用仅为后者的25%，为复杂场景下的精准检测提供实用解决方案。
Abstract: As a key preprocessing step of recognition technology, the accuracy of face detection is easily affected by complex environment. In this paper, an interactive improved interface based on MATLAB is proposed for the traditional Viola-Jones algorithm. The Haar feature template is used to extract the multi-level structural features of the face, and the cascade classifier is used to achieve fast region screening. An adaptive threshold adjustment mechanism is designed to allow users to adjust the detection sensitivity of facial features through the Graphical User Interface interface. Finally, the integrated detection system supports multi-site independent detection and result visualization. The experiment is verified by ORL and WIDER FACE database. The results show that in the single face scene, the face detection rate is 100 %, and the eyes, nose and mouth are 92.5 %, 97.5 % and 95 % respectively. The face detection rate in the multi-person scene is 96.36 %, which is 12.7 % higher than that in the fixed threshold mode. The comprehensive performance is close to the MTCNN model, and the memory usage is only 25 % of the latter, which provides a practical solution for accurate detection in complex scenes.
苏晓, 吕睿星. 基于MATLAB GUI的人脸检测算法[J]. 吉林化工学院学报, 2026, 43(1): 88-94.
SU Xiao, LV Ruixing. Face Detection Algorithm based on MATLAB GUI. Journal of Jilin Institute of Chemical Technology, 2026, 43(1): 88-94.
