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Title: Research Into Illumination Variance In Video Processing
Other Titles: Illumination Variance In Video Processing
Authors: Javadi, Seyed Mahdi Sadreddinhajseyed
Advisors: Li, Y
Liu, X
Keywords: Shadow detection and removal;Cloud detection and removal;Reflectance and glare detection;Video and image processing
Issue Date: 2018
Publisher: Brunel University London
Abstract: Inthisthesiswefocusontheimpactofilluminationchangesinvideoand we discuss how we can minimize the impact of illumination variance in video processing systems. Identifyingandremovingshadowsautomaticallyisaverywellestablished and an important topic in image and video processing. Having shadowless image data would benefit many other systems such as video surveillance, tracking and object recognition algorithms. Anovelapproachtoautomaticallydetectandremoveshadowsispresented in this paper. This new method is based on the observation that, owing to the relative movement of the sun, the length and position of a shadow changes linearly over a relatively long period of time in outdoor environments,wecanconvenientlydistinguishashadowfromotherdark regions in an input video. Then we can identify the Reference Shadow as the one with the highest confidence of the mentioned linear changes. Once one shadow is detected, the rest of the shadow can also be identifiedandremoved. Wehaveprovidedmanyexperimentsandourmethod is fully capable of detecting and removing the shadows of stationary and moving objects. Additionally we have explained how reference shadows can be used to detect textures that reflect the light and shiny materials such as metal, glass and water. ...
Description: Doctor of Philosophy and was awarded by Brunel University London
Appears in Collections:Computer Science
Dept of Computer Science Theses

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