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Infrared Image Pedestrian Detection Techniques with Quantitative Analysis

  • Rajkumar Soundrapandiyan
  • K. C. SantoshEmail author
  • P. V. S. S. R. Chandra MouliEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1037)

Abstract

Pedestrian detection in infrared (IR) images is important due to widely used IR images in many applications including surveillance, night vision, searching, environmental monitoring, driving assistant system etc. Among these pedestrian detection in defense gained more attention in the infrared images. However, there are still many problems existed in pedestrian detection in infrared images are low signal to noise ratio, low contrast, complex background, pedestrians are prone to occluded by other things and lack of shape. In this paper, Global background subtraction, adaptive filter and local adaptive thresholding based Pedestrian Detection method proposed to overcome these problems. Further, the proposed method tested on the OSU thermal pedestrian database. In addition, proposed method result is compared along with the popular existing traditional methods using quantitative measures. From experimental results deduced that the proposed method earned excellent detection rate when compared to other methods.

Keywords

Pedestrian detection Infrared images Thresholding Mean Variance Histogram Misclassification error Relative foreground area error 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringVellore Institute of TechnologyVelloreIndia
  2. 2.Department of Computer ScienceUniversity of South DakotaVermillionUSA
  3. 3.Department of Computer ApplicationsNIT JamshedpurJamshedpurIndia

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