|Table of Contents|

A CNN-based Approach to Footprint Image Retrieval and Matching(PDF)

南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2018年03期
Page:
39-
Research Field:
人工智能算法与应用专栏
Publishing date:

Info

Title:
A CNN-based Approach to Footprint Image Retrieval and Matching
Author(s):
Chen Yang12Zeng Cheng3Cheng Cheng1Zou Encen1Gu Jianwei12Lu You1Xi Xuefeng12
(1.School of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou 215009,China)(2.Suzhou Key Laboratory of Virtual Reality and Intelligent Interaction,Suzhou University of Science and Technology,Suzhou 215009,China)(3.Command Center of Kunshan Public Security Bureau,Suzhou 215300,China)
Keywords:
deep learningconvolutional neural networkfootprint searchingimage processing
PACS:
TP183
DOI:
10.3969/j.issn.1672-1292.2018.03.006
Abstract:
Footprint images,as one of the important evidences of crime scenes,can’t be ignored in the cracking of serial cases. Traditional footprint comparison and retrieval require a lot of time and manpower,greatly affecting the progress of the case. Convolutional Neural Network(CNN)has shown good results in image recognition and retrieval. In order to meet the actual needs of public security footprint image retrieval,this paper proposes an approach to footprint image retrievaling and matching based on convolutional neural network,and sets different search areas for search results to meet different business requirements. Preliminary experiments show that the proposed approach is effective and practical.

References:

[1] 李钊,卢苇,邢薇薇,等. CNN视觉特征的图像检索[J]. 北京邮电大学学报,2015,38(增刊1):103-106.
LI Z,LU W,XING W W,et al. Image retrieval based on CNN visual features[J]. Journal of Beijing university of posts and telecommunications,2015,38(Suppl. 1):103-106.(in Chinese)
[2]胡二雷,冯瑞. 基于深度学习的图像检索系统[J]. 计算机系统应用,2017,26(3):8-19.
HU E L,FENG R. Image retrieval system based on deep learning[J]. Computer systems and applications,2017,26(3):8-19.(in Chinese)
[3]朱煜,赵江坤,王逸宁,等. 基于深度学习的人体行为识别算法综述[J]. 自动化学报,2016,42(6):848-857.
ZHU Y,ZHAO J K,WANG Y N,et al. A review of human action recognition based on deep learning[J]. Acta automatica sinica,2016,42(6):848-857.(in Chinese)
[4]周晔,张军平. 基于多尺度深度学习的商品图像检索[J]. 计算机研究与发展,2017,54(8):1824-1832.
ZHOU Y,ZHANG J P. Multi-scale deep learning for product image search[J]. Journal of computer research and development,2017,54(8):1824-1832.(in Chinese)
[5]韩科. 应用模糊BP神经网络对足迹图像识别方法的研究[D]. 沈阳:东北大学,2006.
HAN K. Research on an automatic toe shape recognition method based on fuzzy comprehensive evaluation model and BP NN clustering[D]. Shenyang:Northeastern university,2006.(in Chinese)
[6]牛瑞娟. 足迹图像的特征提取与分类[D]. 青岛:山东科技大学,2007.
NIU R J. Study of the feature extraction and classification of footprint images[D]. Qingdao:Shandong university of science and technology,2007.(in Chinese)v[7]周飞燕,金林鹏,董军. 卷积神经网络研究综述[J]. 计算机学报,2017,40(6):1229-1251.
ZHOU F Y,JIN L P,DONG J. Review of convolutional neural network[J]. Chinese journal of computers,2017,40(6):1229-1251.(in Chinese)
[8]FU R,LI B,GAO Y,et al. Content-based image retrieval based on CNN and SVM[C]//IEEE International Conference on Computer and Communications. Chengdu,China,2016.
[9]SEDDATI O,DUPONT S,MAHMOUDI S,et al. Towards good practices for image retrieval based on CNN features[C]//IEEE International Conference on Computer Vision Workshop. Venice,Italy,2017.
[10]陈宏彩,程煜,张常有.卷积神经网络在车辆目标快速检测中的应用[J]. 软件学报,2017,28(增刊1):107-114.
CHEN H C,CHENG Y,ZHANG C Y. Convolutional neural network applied on fast vehicle objects detection[J]. Journal of software,2017,28(Suppl. 1):107-114.(in Chinese)
[11]SCHROFF F,KALENICHENKO D,PHILBIN J. Facenet:a unified embedding for face recognition and clustering[C]//IEEE Conference on Computer Vision and Pattern Recognition. Boston,USA,2015.
[12]WANG J Y,QIAN Y,YE Q Q,et al. Image retrieval method based on metric learning for convolutional neural network[C]//International Seminar on Advances in Materials Science and Engineering. Singapore,2017.
[13]RADENOVIC F,TOLIAS G,CHUM O. Fine-tuning CNN image retrieval with no human annotation[DB/OL].(2018-06-08). https://arxiv.org/abs/1711.02512v1.
[14]金连文,钟卓耀,杨钊,等. 深度学习在手写汉字识别中的应用综述[J]. 自动化学报,2016,42(8):1125-1141.
JIN L W,ZHONG Z Y,YANG Z,et al. Applications of deep learning for handwritten Chinese character recognition:a review[J]. Acta automatica sinica,2016,42(8):1125-1141.(in Chinese)
[15]BABENKO A,SLESAREV A,CHIGORIN A,et al. Neural codes for image retrieval[C]//European conference on computer vision. Zurich,Switzerland,2014.

Memo

Memo:
-
Last Update: 2018-09-30