An Efficient Algorithm for Real-Time Object Detection in Images

Authors(2) :-Md. Samiul Islam, Samia Sultana

In this paper we have proposed an algorithm for object detection in various situations. Nowadays object detection and recognition has entered in every sphere of life in one or the other form. Applications of object detection are video surveillance, anti-theft system using cameras, face-recognition, biometric verification etc. Research are going on how to improve the performance in term of space and time complexity, how to deal with adverse conditions like improper lightning conditions, scene clutter, occlusion etc. and to reduce false positive rate etc. In this paper we have explained how to deal with the any situation while acquiring the images so that it can be used for better scene interpretation. Results have been generated using flash of light and dark region present in the image as some of the adverse situations. Here we have trained the system to detect the object using our algorithm. The algorithm is simple and very useful as it reduces the false positive rate as compared to contemporary algorithms and increases the efficiency of applications like video surveillance and scene interpretation etc.

Authors and Affiliations

Md. Samiul Islam
Stamford University Bangladesh, Dhaka, Bangladesh
Samia Sultana
Stamford University Bangladesh, Dhaka, Bangladesh

Object Detection, Image Classification, Image Recognition, Histogram of Oriented Gradients, Support Vector Machine.

Publication Details

Published in : Volume 4 | Issue 8 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 640-645
Manuscript Number : IJSRSET1848148
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Md. Samiul Islam, Samia Sultana, " An Efficient Algorithm for Real-Time Object Detection in Images, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.640-645, May-June-2018.
Journal URL : http://ijsrset.com/IJSRSET1848148

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