Repository logo
 
Publication

Image enhancement for underwater mining applications

dc.contributor.advisorMartins, Alfredo Manuel Oliveira
dc.contributor.authorRajesh, Shravan Dev
dc.date.accessioned2020-04-01T14:10:43Z
dc.date.available2020-04-01T14:10:43Z
dc.date.issued2019
dc.description.abstractThe exploration of water bodies from the sea to land filled water spaces has seen a continuous increase with new technologies such as robotics. Underwater images is one of the main sensor resources used but suffer from added problems due to the environment. Multiple methods and techniques have provided a way to correct the color, clear the poor quality and enhance the features. In this thesis work, we present the work of an Image Cleaning and Enhancement Technique which is based on performing color correction on images incorporated with Dark Channel Prior (DCP) and then taking the converted images and modifying them into the Long, Medium and Short (LMS) color space, as this space is the region in which the human eye perceives colour. This work is being developed at LSA (Laboratório de Sistema Autónomos) robotics and autonomous systems laboratory. Our objective is to improve the quality of images for and taken by robots with the particular emphasis on underwater flooded mines. This thesis work describes the architecture and the developed solution. A comparative analysis with state of the art methods and of our proposed solution is presented. Results from missions taken by the robot in operational mine scenarios are presented and discussed and allowing for the solution characterization and validation.pt_PT
dc.identifier.tid202343898pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/15696
dc.language.isoengpt_PT
dc.subjectUnderwater Imagespt_PT
dc.subjectImage processingpt_PT
dc.subjectImage enhancementpt_PT
dc.subjectColor correctionpt_PT
dc.subjectComputer visionpt_PT
dc.subjectUnderwater robotspt_PT
dc.subjectUnderwater miningpt_PT
dc.titleImage enhancement for underwater mining applicationspt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Engenharia Eletrotécnica e de Computadores - Sistemas Autónomospt_PT

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
DM_Shravan Dev Rajesh_2019_MEEC.pdf
Size:
18.62 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: