Pedestrian Segmentation in Infrared Images Based on Local Autocorrelation

被引：0
|
作者：
Wu, Tao [1 ,2 ]
Zeng, Shaogeng [2 ]
Yang, Junjie [1 ,2 ]
机构：
[1] Guangdong Engn & Technol Dev Ctr E learning, 29 Cunjin Rd, Zhanjiang 524048, Peoples R China
[2] Lingnan Normal Univ, Sch Informat Sci & Technol, 29 Cunjin Rd, Zhanjiang 524048, Peoples R China
来源：
EIGHTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2016) | 2016年 / 10033卷
关键词：
Image thresholding; image segmentation; infrared image processing; Moran's I; feature fusion;
D O I：
10.1117/12.2243727
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In order to select the optimal threshold for pedestrian segmentation in infrared images, a novel algorithm based on local autocorrelation is proposed. The algorithm calculates the local autocorrelation feature of a given image. Next, it constructs a new feature matrix based on this spatial correlation and the original grayscale. Then, it obtains an automatic threshold related with local combined features using the geometrical method based on histogram analysis. Finally, it extracts the image region of pedestrian and yields the binary result. It is indicated by the experiments that, the proposed method performs good result of pedestrian region extraction and thresholding, and it is reasonable and effective.
引用
收藏
页数：6
相关论文
共 50 条
  • [31] Method research on vehicular infrared pedestrian detection based on local features
    Wang, Guo-Hua
    Liu, Qiong
    Zhuang, Jia-Jun
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2015, 43 (07): : 1444 - 1448
  • [32] Pedestrian detection and tracking in near infrared images
    Tabuse, Masayoshi
    Kozawa, Sayuri
    PROCEEDINGS OF THE SEVENTEENTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 17TH '12), 2012, : 200 - 203
  • [33] Pedestrian detection and tracking in far infrared images
    Yasuno, M
    Ryousuke, S
    Yasuda, N
    Aoki, M
    2005 IEEE Intelligent Transportation Systems Conference (ITSC), 2005, : 131 - 136
  • [34] Target Detection and Pedestrian Recognition in Infrared Images
    Wang, Jiabao
    Zhang, Yafei
    Lu, Jianjiang
    Li, Yang
    JOURNAL OF COMPUTERS, 2013, 8 (04) : 1050 - 1057
  • [35] Pedestrian Classification and Detection in Far Infrared Images
    Khellal, Atmane
    Ma, Hongbin
    Fei, Qing
    INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2015, PT I, 2015, 9244 : 511 - 522
  • [36] Marker-based watershed algorithm for segmentation of the infrared images
    Manda, Manikanta Prahlad
    Park, ChanSu
    Oh, Byeong Cheol
    Kim, Hi-Seok
    2019 INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC), 2019, : 227 - 228
  • [37] Target Segmentation Algorithm Based on Toboganning Method in Infrared Images
    Kim, Jae Hyup
    Jun, Gab Song
    2009 34TH INTERNATIONAL CONFERENCE ON INFRARED, MILLIMETER, AND TERAHERTZ WAVES, VOLS 1 AND 2, 2009, : 372 - 373
  • [38] Fusion of Infrared and Visible Light Images Based on Region Segmentation
    Liu Kun
    Guo Lei
    Li Huihui
    Chen Jingsong
    CHINESE JOURNAL OF AERONAUTICS, 2009, 22 (01) : 75 - 80
  • [39] Segmentation Algorithms for Ground-Based Infrared Cloud Images
    Terren-Serrano, Guillermo
    Martinez-Ramon, Manel
    2021 IEEE PES INNOVATIVE SMART GRID TECHNOLOGY EUROPE (ISGT EUROPE 2021), 2021, : 7 - 12
  • [40] Fusion of Infrared and Visible Light Images Based on Region Segmentation
    Kun, Liu
    Lei, Guo
    Huihui, Li
    Jingsong, Chen
    Chinese Journal of Aeronautics, 2009, 22 (01): : 75 - 80
12345