Neural network based image object detection and tracking for security and surveillance

Sethi, Nishu; Bajaj, Shalini Bhaskar

doi:10.47974/JDMSC-1780

Open Access Research Article

Neural network based image object detection and tracking for security and surveillance

^*Nishu SethiCorresponding authorsethinishu@gmail.comDepartment of Computer Science and EngineeringAmity School of Engineering and TechnologyHaryanaAmity UniversityIndiaView full profile → , Shalini Bhaskar Bajajsbhaskarbajaj@ggn.amity.eduDepartment of Computer Science and EngineeringAmity School of Engineering and TechnologyHaryanaAmity UniversityIndiaView full profile →

* Corresponding author · click or hover a name for details

pp. 939–949Vol. 26Issue 3April 2023DOI: 10.47974/JDMSC-1780 Crossmark XML

Published Online:: 01 Apr 2023
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-1780
Pages:: 939–949

Abstract

The saliency map obtained from the source image determines the efficacy of the traditional seam carving process. The importance map proposed in this paper is used to highlight the shadows and important objects in the images. It combines the saliency map, shadow map, and gradient map acquired from the image to discover the image’s prominent regions. The proposed map, when compared to others, highlights more distinct details with the state-of-the-art. The improved seam carving technique is paired with cropping and warping image retargeting operators in the suggested hybrid sequence. By labelling a picture with a class label and object localisation, the coordinates of the objects are generated using R-CNN object detection techniques. This will help in identifying the non-salient objects from the image for security and surveillance purposes with pin-point accuracy.

Keywords

Importance map Seam carving Image retargeting Gradient map Object detection

Subject Classifications

Primary 93A30Secondary 49K15

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