Speech biological Hash retrieval algorithm based on Lu's feature security template

被引:0
|
作者
Huang, Yibo [1 ]
Wang, Ning [1 ]
Zhang, Qiuyu [2 ]
机构
[1] College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou,730070, China
[2] School of Computer and Communication, Lanzhou University of Technology, Lanzhou,730050, China
关键词
Bioinformatics - Feature extraction - Hash functions;
D O I
10.13245/j.hust.239431
中图分类号
学科分类号
摘要
To improve the protection of speech features and the diversity of biological Hash construction process,and address the problem that the existing speech biological Hash retrieval algorithm could not form effective protection of speech features due to the single Hash construction process,a speech biological Hash retrieval algorithm based on Lu's feature security template was proposed.First,gammatone cepstral coefficient (GTCC) algorithm was used to extract the audio features of the original speech,and Toeplitz and cyclic measurement matrix were used to reduce the dimension of the audio features.Then,the dimensionally reduced feature vectors were processed differentially and classified by support vector machine (SVM).According to the classification results,one to one corresponding key was generated,and the key was used as the initial value of Lu's chaos mapping to construct the Lu's feature security template of corresponding key. Finally,the feature vectors after dimensionality reduction were quantized by the corresponding Lu's feature security template to obtain the biological Hash.Experimental results show that the proposed security template can improve the security and diversity of the biological Hash construction process. Meanwhile,the biological Hash generated by the security template has good differentiation and robustness,and can maintain the retrieval of operational speech for volume adjustment,filtering,resample and format compression. © 2023 Huazhong University of Science and Technology. All rights reserved.
引用
收藏
页码:60 / 66
相关论文
共 50 条
  • [41] Verifiable speech retrieval algorithm based on KNN secure hashing
    Li An
    Yi-bo Huang
    Qiu-yu Zhang
    Multimedia Tools and Applications, 2023, 82 : 7803 - 7824
  • [42] Fast Retrieval Method of Massive Library Literature Resources Based on an Online Hash Algorithm
    Wang, Huan
    JOURNAL OF TESTING AND EVALUATION, 2023, 51 (03) : 1543 - 1554
  • [43] RESEARCH ON ENGLISH READING EMOTIONAL BEHAVIOR RETRIEVAL BASED ON MULTITASKING HASH LEARNING ALGORITHM
    Wu, Hao
    MEDICINE, 2024, 103 (14)
  • [44] A fast, feature-based cluster algorithm for information retrieval
    Mehlitz, Martin
    Bauckhage, Christian
    Albayrak, Sahin
    IRI 2007: PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION, 2007, : 335 - +
  • [45] An Improved Algorithm Based on Color Feature Extraction for Image Retrieval
    Li, Mengzhe
    Jiang, Xiuhua
    2016 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC), VOL. 2, 2016, : 281 - 285
  • [46] Feature of Statistical Projection Algorithm-based Image Retrieval
    Zheng, Xiaofei
    Gao, Zhe
    Luo, Wei
    APPLIED MATHEMATICS & INFORMATION SCIENCES, 2014, 8 (02): : 721 - 725
  • [47] Research on a Scale-Based Feature Image Retrieval Algorithm
    Zhang, Haijian
    Sun, Dan
    PROCEEDINGS OF 2023 7TH INTERNATIONAL CONFERENCE ON ELECTRONIC INFORMATION TECHNOLOGY AND COMPUTER ENGINEERING, EITCE 2023, 2023, : 414 - 418
  • [48] An Improved Algorithm Based on Texture Feature Extraction for Image Retrieval
    Zhang, He
    Jiang, Xiuhua
    2015 12TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD), 2015, : 1270 - 1274
  • [49] Image Security Retrieval Based on Chaotic Algorithm and Deep Learning
    Zhang, Qing
    Yan, Yong
    Lin, Yong
    Li, Yan
    IEEE ACCESS, 2022, 10 : 67210 - 67218
  • [50] Hybrid encryption method for biological information database based on AES and hash algorithm
    Yan, Han-Chi
    Su, Chun-Lin
    Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2024, 54 (10): : 2994 - 2999