Thesis (MSc)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Range images are images that store at each pixel the distance between the sensor and a particular point in the observed scene, instead of the colour information. They provide a convenient storage format for 3-D point cloud information captured from a single point of view. Range image segmentation is the process of grouping the pixels of a range image into regions of points that belong to the same surface. Segmentations are useful for many applications that require higherlevel information, and with range images they also represent a significant step towards complete scene reconstruction. This study considers the segmentation of range images into planar surfaces. It discusses the theory and also implements and evaluates some current approaches found in the literature. The study then develops a new approach based on the theory of graph cut optimization which has been successfully applied to various other image processing tasks but, according to a search of the literature, has otherwise not been used to attempt segmenting range images. This new approach is notable for its strong guarantees in optimizing a specific energy function which has a rigorous theoretical underpinning for handling noise in images. It proves to be very robust to noise and also different values of the few parameters that need to be trained. Results are evaluated in a quantitative manner using a standard evaluation framework and datasets that allow us to compare against various other approaches found in the literature. We find that our approach delivers results that are competitive when compared to the current state-of-the-art, and can easily be applied to images captured with different techniques that present varying noise and processing challenges. / AFRIKAANSE OPSOMMING: Dieptebeelde is beelde wat vir elke piksel die afstand tussen die sensor en ’n spesifieke punt in die waargenome toneel, in plaas van die kleur, stoor. Dit verskaf ’n gerieflike stoorformaat vir 3-D puntwolke wat vanaf ’n enkele sigpunt opgeneem is. Die segmentasie van dieptebeelde is die proses waarby die piksels van ’n dieptebeeld in gebiede opgedeel word, sodat punte saam gegroepeer word as hulle op dieselfde oppervlak lê. Segmentasie is nuttig vir verskeie toepassings wat hoërvlak inligting benodig en, in die geval van dieptebeelde, verteenwoordig dit ’n beduidende stap in die rigting van volledige toneel-rekonstruksie. Hierdie studie ondersoek segmentasie waar dieptebeelde opgedeel word in plat vlakke. Dit bespreek die teorie, en implementeer en evalueer ook sekere van die huidige tegnieke wat in die literatuur gevind kan word. Die studie ontwikkel dan ’n nuwe tegniek wat gebaseer is op die teorie van grafieksnit-optimering wat al suksesvol toegepas is op verskeie ander beeldverwerkingsprobleme maar, sover ’n studie op die literatuur wys, nog nie gebruik is om dieptebeelde te segmenteer nie. Hierdie nuwe benadering is merkbaar vir sy sterk waarborge vir die optimering van ’n spesifieke energie-funksie wat ’n sterk teoretiese fondasie het vir die hantering van geraas in beelde. Die tegniek bewys om fors te wees tot geraas sowel as die keuse van waardes vir die min parameters wat afgerig moet word. Resultate word geëvalueer op ’n kwantitatiewe wyse deur die gebruik van ’n standaard evalueringsraamwerk en datastelle wat ons toelaat om hierdie tegniek te vergelyk met ander tegnieke in die literatuur. Ons vind dat ons tegniek resultate lewer wat mededingend is ten opsigte van die huidige stand-van-die-kuns en dat ons dit maklik kan toepas op beelde wat deur verskeie tegnieke opgeneem is, alhoewel hulle verskillende geraastipes en verwerkingsuitdagings bied.

<p>Laser scanners in combination with devices for accurate orientation like Coordinate Measuring Machines (CMM) are often used in Geometric Reverse Engineering (GRE) to measure point data. The industrial robot as a device for orientation has relatively low accuracy but the advantage of being numerically controlled, fast, flexible, rather cheap and compatible with industrial environments. It is therefore of interest to investigate if it can be used in this application.</p><p>This thesis will describe a measuring system consisting of a laser profile scanner mounted on an industrial robot with a turntable. It will also give an introduction to Geometric Reverse Engineering (GRE) and describe an automatic GRE process using this measuring system. The thesis also presents a detailed accuracy analysis supported by experiments that show how 2D profile data can be used to achieve a higher accuracy than the basic accuracy of the robot. The core topic of the thesis is the investigation of a new technique for planar segmentation. The new method is implemented in the GRE system and compared with an implementation of a more traditional method.</p><p>Results from practical experiments show that the new method is much faster while equally accurate or better.</p>

Laser scanners in combination with devices for accurate orientation like Coordinate Measuring Machines (CMM) are often used in Geometric Reverse Engineering (GRE) to measure point data. The industrial robot as a device for orientation has relatively low accuracy but the advantage of being numerically controlled, fast, flexible, rather cheap and compatible with industrial environments. It is therefore of interest to investigate if it can be used in this application. This thesis will describe a measuring system consisting of a laser profile scanner mounted on an industrial robot with a turntable. It will also give an introduction to Geometric Reverse Engineering (GRE) and describe an automatic GRE process using this measuring system. The thesis also presents a detailed accuracy analysis supported by experiments that show how 2D profile data can be used to achieve a higher accuracy than the basic accuracy of the robot. The core topic of the thesis is the investigation of a new technique for planar segmentation. The new method is implemented in the GRE system and compared with an implementation of a more traditional method. Results from practical experiments show that the new method is much faster while equally accurate or better.