Reveiw of Developed Object Detection Techniques for Auto Detection System

Authors

  • Anita Singh Instruments Research & Development Establishment Defence Research and Development Organization Ministry of Defence, Dehradun-248008, Uttarakhand, India and Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
  • Rajesh Kumar Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
  • R. P. Tripathi Graphic Era Deemed to be University, Dehradun, Uttarakhand, India

Keywords:

Vehicle Detection, Classification, Background Subtraction, Surveillance, Feature Extraction.

Abstract

The automatic detection has emerged as a technique in a realistic manner within the field of automation. This is
very useful in defence as well as civil sector. The main objective of the paper is to model, simulate and analyse
Automatic Target Detection and Shooting (ATDS) of objects, used for target acquisition, tracking, detection and
shooting. The proposed paper can be divided into the following techniques:
 Improvised parametric ratios algorithm for blob analysis of object recognition.
 Feature based target classification algorithm.
 Analysis of different data samples for classification by Bag of feature technique.
 Algorithm for imprecise test detector, HOG-SVM classifier technique.
This system has the ability to classify the physically existing objects like tank, jeep, tetra truck in real time using
thermal imaging cameras during night time as well as in bad weather conditions. The Analysis of all techniques
are provided in tabular form

Downloads

Download data is not yet available.

References

Bhanu, B., & Jones, T. L. (1993). Image understanding research for automatic target recognition. IEEE

Aerospace and Electronic Systems Magazine, 8(10), 15-23.

Burden, M. J. J., & Bell, M. G. H. (1997). Vehicle classification using stereo vision. Proc. Sixth International

Conference on Image Processing and Its Applications, 1997, vol. 2, pp 881-885.

Gonzalez, R. C., & Woods, R. E. (2007). Image processing. Digital image processing, 2nd Edition, Prentice

Hall, 2002.

Gupte, S., Masoud, O., & Papanikolopoulos, P. (2000). Vision-based vehicle classification. In Intelligent

Transportation Systems, 2000. Proceedings. 2000 IEEE (pp. 46-51). IEEE.

Lai, A. H., & Yung, N. H. C. (2000). Vehicle-type identification through automated virtual loop assignment and

block-based direction-biased motion estimation. IEEE Transactions on Intelligent Transportation Systems, 1(2),

-97.

Qihang, Z., Cheng, D., Qifan, Z., & Naiming, Q. (2015, September). The trajectory of anti-ship ballistic missile

design and simulation. In Instrumentation and Measurement, Computer, Communication and Control (IMCCC),

Fifth International Conference on (pp. 373-377). IEEE.

Walters, R. K. (1967). Numerical integration methods for ballistic rocket trajectory simulation programs. Army

Electronics Command White Sands Missile Range Nm Atmospheric Sciences Lab., New Mexico

Yung, N. H., Pang, G. K., & Fung, G. S. (2000). A novel camera calibration technique for visual traffic

surveillance. In Proc (Vol. 40).

Downloads

Published

2023-02-28

How to Cite

Singh, A., Kumar, R., & Tripathi, R. P. (2023). Reveiw of Developed Object Detection Techniques for Auto Detection System. Journal of Graphic Era University, 6(2), 231–237. Retrieved from https://riverpublishersjournal.com/index.php/JGEU/article/view/79

Issue

Section

Articles