High Dynamic Range Object Detection System with Image Fusion Network Using High-Illumination Specialized Binary Image

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This study presents an object detection system combining a dual-imaging CMOS image sensor (CIS) with a fusion model to address feature loss from light saturation. The CIS captures general and binary images, with the latter providing additional information in saturated conditions. These images are fused to preserve texture details and enhance detection under high-intensity lighting. Using the PascalRaw dataset, the proposed system demonstrates robust performance across various lighting conditions, significantly outperforming traditional methods. This research highlights the effectiveness of machine-friendly sensors and fusion models in improving object detection accuracy.

Original languageEnglish
Title of host publication2024 IEEE Sensors, SENSORS 2024 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350363517
DOIs
StatePublished - 2024
Event2024 IEEE Sensors, SENSORS 2024 - Kobe, Japan
Duration: 20 Oct 202423 Oct 2024

Publication series

NameProceedings of IEEE Sensors
ISSN (Print)1930-0395
ISSN (Electronic)2168-9229

Conference

Conference2024 IEEE Sensors, SENSORS 2024
Country/TerritoryJapan
CityKobe
Period20/10/2423/10/24

Keywords

  • Binary Image
  • Deep Learning
  • High Dynamic Range
  • High-illumination Condition
  • Image Fusion Model
  • Object Detection System

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