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山东大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 27-36.doi: 10.6040/j.issn.1672-3961.0.2018.072

• 机器学习与数据挖掘 • 上一篇    下一篇

基于PDEs的图像特征提取方法

江珊珊,杨静*,范丽亚   

  1. 聊城大学数学科学学院, 山东 聊城 252059
  • 收稿日期:2018-02-09 出版日期:2018-08-20 发布日期:2018-02-09
  • 通讯作者: 杨静(1986— ),女,山东聊城人,讲师,博士,主要研究方向为模式识别理论与应用,机器学习理论与应用. ;E-mail: yangjing860204@163.com E-mail:jiangshanshan102@163.com
  • 作者简介:江珊珊(1995— ),女,山东青岛人,硕士研究生,主要研究方向为机器学习理论与应用,模式识别. E-mail:jiangshanshan102@163.com
  • 基金资助:
    山东省自然科学基金资助项目(ZR2016AM24,ZR2018BF010);聊城大学博士基金资助项目(318051715)

An image feature extraction method based on PDEs

JIANG Shanshan, YANG Jing*, FAN Liya   

  1. School of Mathematical Sciences, Liaocheng University, Liaocheng 252059, Shandong, China
  • Received:2018-02-09 Online:2018-08-20 Published:2018-02-09

摘要: 针对提取图像判别信息的基于偏微分方程(partial differential equations, PDEs)的方法做了进一步研究。研究进化次数对图像特征质量的影响和压缩函数的压缩速度对图像特征质量的影响。试验结果表明:PDEs的进化可以降低遮挡的影响以及对光暗具有鲁棒性,但PDEs的进化次数以及压缩函数和压缩速度严重影响图像特征质量。

关键词: 偏微分方程, 压缩函数, 图像特征, 遮挡, 进化次数

Abstract: Further research was conducted on image feature extraction method based on partial differential equations(PDEs). The effect of evolution times on quality of feature, and the reflection of compression function on the quality of feature were studied. Experiment results indicated that the evolution of PDEs could reduce the impact of occlusion and be robust to dark light, but the qualities of the image features could be seriously affected by evolution times of PDEs and compression function and compression speed.

Key words: partial differential equation, occlusion, compression functions, evolution time, image feature

中图分类号: 

  • TP391
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