Detecting regions of change while reducing unimportant changes in multiple outdoor images of the same scene containing fence wires (i.e., a chain-link mesh fence) acquired by a mobile camera from slightly different viewing positions, angles and at different times is a very difficult problem. Regions of change include appearing of new objects and/or disappearing of old objects behind fence wires, breaches in the integrity of fence wires and attached objects in front of fence wires. Unimportant changes are mainly caused by camera movement, considerable background clutter, illumination variation, tiny sizes of fence wires and non-uniform illumination that occurs across fence wires. There are several issues that arise from these kinds of multiple outdoor images. The issues are: (1) parallax (the apparent displacement of an object as seen from two different positions that are not on a line with the object) among objects in the scene, (2) changing in size of same objects as a result of camera movement in forward or backward direction, (3) background clutter of outdoor scenes, (4) thinness of fence wires and (5) significant illumination variation that occurs in outdoor scenes and across fence wires. In this dissertation, an automated change detection method is proposed for these kinds of multiple outdoor images. The change detection method is composed of two distinct modules, which are a module for detecting object presence and/or absence behind fence wires and another module for detecting breaches in the integrity of fence wires and/or attached objects in front of fence wires. The first module consist of five main steps: (1) automated image registration, (2) confidence map image production by the Zitnick and Kanade algorithm, (3) occlusion map image generation, (4) significant or unimportant changes decision by the first hybrid decision-making system and (5) false positives reduction by the template subtraction approach. The second module integrates: (1) the Sobel edge detector combined with an adaptive thresholding technique in extracting edges of fence wires, (2) an area-based measuring in separating small and big objects based on their average areas determined once in the calibration process and (3) the second hybrid decision-making system in classifying objects as significant or unimportant changes. Experimental results demonstrate that the change detection method can identify and indicate approximate locations and possible percentages of significant changes whilst reducing unimportant changes in these kinds of multiple outdoor images. The study has utilized occluded regions in a confidence map image produced by the Zitnick and Kanade algorithm as potential significant changes in the image change detection research. Moreover, the study proves that the use of the Sobel edge detector combined with an adaptive thresholding technique is applicable in extracting edges of outdoor fence wires. In the future, the method could be integrated into patrol robots in order to provide assistance to human guards in protecting outdoor perimeter security. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1522689 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2010

Genom århundraden har bilden varit en viktig del i vårt samhälle. Den har varit en källa till underhållning, sparande av minnen och även ett sätt att kommunicera på. Bilder har använts på många olika sätt och sedan 1800-talet har vi kunnat fånga bilder genom fotografier. Med den teknik vi har i dag, kan bilder tas och delas via mobiltelefonen och på grund av detta har fotodelning ökat snabbt. Inte bara genom att vi nu har ett urval av olika fotodelningsapplikationer, utan de erbjuder även verktyg för att retuschera bilder innan de delas vidare med fördefinierade filter för enkel redigering. Vi var därför intresserade av hur dessa verktyg påverkat vårt sätt att retuschera bilder. Med det menar vi om möjligheten att använda filter förändrat hur vi tänker om retuschering och om detta spelat roll i vårt sätt att dela bilder. Resultat från enkät och intervjustudierna har visat att majoriteten av de foton som delas går genom någon form av retuschering. Vare sig det är genom fördefinierade filter eller om de redigeras manuellt finns det mycket få användare av fotodelningsapplikationer som delar oredigerade bilder. Vidare har det visat sig, som en effekt av filterfunktionen, att fler människor introduceras för konsten att redigera. / Through centuries the picture has been an important element in our community. It’s been a source to entertainment, memory sharing and also a way of communication. Pictures have been used in many ways and since the 19th century we have been able to capture pictures on photos. With the technology we have today, pictures can be taken and shared via the cellphone and because of this the photo-sharing have increased rapidly. Not only do we now have a selection of different photo-sharing networks they also offer tools to retouch the photos before sharing with predefined filters for easy editing. We were therefore interested in how these tools influence the way we retouch our photos. By that we mean if the opportunity to use filter affect how we think about retouching and if this affect the way we share our photos. By questionnaire and interview study, the result showed us that the majority of the photos that are being shared are going through some kind of retouches. Whether it is by predefined filters or if they are manually edited there are very few users of photo-sharing networks who shares unedited photos. Further it has merged that because of the filter function, more people are being introduced to the art of editing.

In this paper, a method for determining ground plane features in a sequence of images captured by a mobile camera is presented. The hardware of the mobile system consists of a monocular camera that is mounted on an inertial measurement unit (IMU). An image processing procedure is proposed, first to extract image features and match them across consecutive image frames, and second to detect the ground plane features using a two-step algorithm. In the first step, the planar homography of the ground plane is constructed using an IMU-camera motion estimation approach. The obtained homography constraints are used to detect the most likely ground features in the sequence of images. To reject the remaining outliers, as the second step, a new plane normal vector computation approach is proposed. To obtain the normal vector of the ground plane, only three pairs of corresponding features are used for a general camera transformation. The normal-based computation approach generalizes the existing methods that are developed for specific camera transformations. Experimental results on real data validate the reliability of the proposed method. / <p>QC 20121107</p>