光学学报, 2020, 40 (13): 1310001, 网络出版: 2020-07-09   

基于超像素分割的IPPG活体皮肤检测 下载: 907次

IPPG Alive-Skin Detection Based on Superpixel Segmentation
作者单位
北京理工大学光电学院精密光电测试仪器与技术北京市重点实验室, 北京 100081
摘要
针对现有活体皮肤检测方法精度不高、实时性较差的问题,提出一种基于超像素分割的成像式光电容积描记(IPPG)活体皮肤检测(SPASD)算法。利用零参数简单线性迭代聚类算法将图像分割为多个超像素子块;然后通过IPPG技术并行提取各子块中的脉搏波信号;最后利用支持向量机对提取到的信号进行训练分类,进而实现活体皮肤的实时检测。实验结果表明,SPASD算法可以有效提高活体皮肤的检测精度和实时性,其检测精度达92.02%。所提方法在人脸防骗、非接触生理信号检测、面部表情识别等领域具有应用前景。
Abstract
The existing alive-skin detection methods exhibit low accuracy and poor real-time performance. Therefore, an image photoplethysmography (IPPG) alive-skin detection (SPASD) algorithm is proposed based on superpixel segmentation in this study. An image is segmented into multiple superpixel sub-blocks using the simple linear iterative clustering zero-parameter algorithm; subsequently, the IPPG technology is used to extract pulse signals from each sub-block in parallel. Finally, a support vector machine is used to train and classify the extracted signals for achieving real-time alive-skin detection. The experimental results demonstrate that the SPASD algorithm can effectively improve the alive-skin detection accuracy (92.02%) and real-time performance. The proposed method can be applied in face anti-fraud, non-contact physiological signal detection, facial expression recognition, and other fields.

孔令琴, 吴育恒, 赵跃进, 董立泉, 刘明, 惠梅. 基于超像素分割的IPPG活体皮肤检测[J]. 光学学报, 2020, 40(13): 1310001. Lingqin Kong, Yuheng Wu, Yuejin Zhao, Liquan Dong, Ming Liu, Mei Hui. IPPG Alive-Skin Detection Based on Superpixel Segmentation[J]. Acta Optica Sinica, 2020, 40(13): 1310001.

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