Literature DB >> 33445557

CMOS Image Sensors in Surveillance System Applications.

Susrutha Babu Sukhavasi1, Suparshya Babu Sukhavasi1, Khaled Elleithy1, Shakour Abuzneid1, Abdelrahman Elleithy2.   

Abstract

Recent technology advances in CMOS image sensors (CIS) enable their utilization in the most demanding of surveillance fields, especially visual surveillance and intrusion detection in intelligent surveillance systems, aerial surveillance in war zones, Earth environmental surveillance by satellites in space monitoring, agricultural monitoring using wireless sensor networks and internet of things and driver assistance in automotive fields. This paper presents an overview of CMOS image sensor-based surveillance applications over the last decade by tabulating the design characteristics related to image quality such as resolution, frame rate, dynamic range, signal-to-noise ratio, and also processing technology. Different models of CMOS image sensors used in all applications have been surveyed and tabulated for every year and application.

Entities:  

Keywords:  CMOS image sensor; dynamic range; frame rate; resolution; signal-to-noise ratio; surveillance systems

Year:  2021        PMID: 33445557     DOI: 10.3390/s21020488

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

1.  Two High-Precision Proximity Capacitance CMOS Image Sensors with Large Format and High Resolution.

Authors:  Yuki Sugama; Yoshiaki Watanabe; Rihito Kuroda; Masahiro Yamamoto; Tetsuya Goto; Toshiro Yasuda; Hiroshi Hamori; Naoya Kuriyama; Shigetoshi Sugawa
Journal:  Sensors (Basel)       Date:  2022-04-04       Impact factor: 3.576

2.  Deep Neural Network Approach for Pose, Illumination, and Occlusion Invariant Driver Emotion Detection.

Authors:  Susrutha Babu Sukhavasi; Suparshya Babu Sukhavasi; Khaled Elleithy; Ahmed El-Sayed; Abdelrahman Elleithy
Journal:  Int J Environ Res Public Health       Date:  2022-02-18       Impact factor: 3.390

3.  A Hybrid Model for Driver Emotion Detection Using Feature Fusion Approach.

Authors:  Suparshya Babu Sukhavasi; Susrutha Babu Sukhavasi; Khaled Elleithy; Ahmed El-Sayed; Abdelrahman Elleithy
Journal:  Int J Environ Res Public Health       Date:  2022-03-06       Impact factor: 3.390

  3 in total

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