计算机技术与发展2019，Vol.29Issue(3)：85-88,4.DOI:10.3969/j.issn.1673-629X.2019.03.018
基于人脸识别的海量图片的存储和索引优化
Storage and Index Optimization of Massive Images Based on Facial Recognition
摘要
Abstract
Face recognition is a technique to identify individuals based on their facial features. The face images are captured by the camera mainly. However, in the process of generating a large number of small files, it is difficult for the distributed file system to provide high performance reading and writing and fast retrieval. In this paper, combining FastDFS, Redis and Mysql to optimize the storage and index of images, small image files in the same camera directory are merged into large files, and internal small file index is established. The resultant large file is then written to FastDFS to generate a large file index. At last, the client combines the small file index with the large file index for generating the full-text index, taking advantage of the Mysql persistent storage characteristics for the storage of file name and corresponding full-text index, using the Redis memory database to temporarily store files and read files for nearly a year, and at the same time, adopting the pre-reading mechanism to pre-fetch the peripheral time files to reduce the operation of IO. Finally, it is proved that the average writing performance is improved by 7.5％, and the average reading performance by 5.0％.关键词
人脸识别/图片小文件/FastDFS/Redis/读写性能Key words
face recognition/image small files/FastDFS/Redis/reading and writing performance分类
信息技术与安全科学引用本文复制引用
蒋园,阳许军..基于人脸识别的海量图片的存储和索引优化[J].计算机技术与发展,2019,29(3):85-88,4.基金项目
湖北省技术创新专项重大项目(2018AAA061) （2018AAA061）
