| 基于OpenCL的人脸识别与隐藏系统 |
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| 引用本文： | 汪方良,施慧彬. 基于OpenCL的人脸识别与隐藏系统[J]. 计算机与现代化, 2016, 0(1): 16. DOI: 10.3969/j.issn.1006-2475.2016.01.004 |
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| 作者姓名： | 汪方良 施慧彬 |
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| 摘 要： | 为加强人脸识别系统的隐私保护，本文引入基于灰度图像改变的加密解密算法对重要识别对象进行保护。为提高人脸识别与加密解密速度，运用OpenCL技术在异构平台下实现单设备与多设备的并行加速。测试结果表明，在使用单GPU时人脸识别局部加速达到1.9x，图像加密加速达到6.65x，而双GPU加速时，前者加速比可达4.11x，后者加速比与单GPU近似。
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| 关 键 词： | 人脸识别 图像加密 并行计算 异构计算 |
| 收稿时间： | 2016-01-26 |
Face Recognition and Hiding System Based on OpenCL |
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| WANG Fang-liang,SHI Hui-bin. Face Recognition and Hiding System Based on OpenCL[J]. Computer and Modernization, 2016, 0(1): 16. DOI: 10.3969/j.issn.1006-2475.2016.01.004 |
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| Authors: | WANG Fang-liang SHI Hui-bin |
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| Abstract: | To strengthen protecting the privacy of the face recognition system, this thesis introduces an algorithm of regarding image encryption based on changing gray-scale to guard significant recognition objectives. Whats more, to speed up the face recognition and image encryption, the thesis uses OpenCL to realize acceleration with single or multiple devices on heterogeneous platform. The test result shows that the local acceleration of face recognition reaches 1.9x and image encryption acceleration is 6.65x when using the single GPU, while the former statistics is 4.11x and the latter data is close to 6.65x when using dual GPU. |
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| Keywords: | face recognition； image encryption； parallel computing； heterogeneous computing |
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