It is well established that acquiring large amounts of range data with vision sensors can quickly lead to important data management challenges where processing capabilities become saturated and pre-empt full usage of the information available for autonomous systems to make educated decisions. While sub-sampling offers a naïve solution for reducing dataset dimension after acquisition, it does not capitalize on the knowledge available in already acquired data to selectively and dynamically drive the acquisition process over the most significant regions in a scene, the latter being generally characterized by variations in depth and surface shape in the context of 3D imaging. This thesis discusses the development of two formal improvement measures, the first based upon surface meshes and Ordinary Kriging that focuses on improving scene accuracy, and the second based upon probabilistic occupancy grids that focuses on improving scene coverage. Furthermore, three selection processes to automatically choose which locations within the field of view of a range sensor to acquire next are proposed based upon the two formal improvement measures. The first two selection processes each use only one of the proposed improvement measures. The third selection process combines both improvement measures in order to counterbalance the parameters of the accuracy of knowledge about the scene and the coverage of the scene. The proposed algorithms mainly target applications using random access range sensors, defined as sensors that can acquire depth measurements at a specified location within their field of view. Additionally, the algorithms are applicable to the case of estimating the improvement and point selection from within a single point of view, with the purpose of guiding the random access sensor to locations it can acquire. However, the framework is developed to be independent of the range sensing technology used, and is validated with range data of several scenes acquired from many different sensors employing various sensing technologies and configurations. Furthermore, the experimental results of the proposed selection processes are compared against those produced by a random sampling process, as well as a neural gas selective sensing algorithm.

In this thesis, I describe a quantitative model that accounts for the circuits and computations of the feedforward path of the ventral stream of visual cortex. This model is consistent with a general theory of visual processing that extends the hierarchical model of (Hubel & Wiesel, 1959) from primary to extrastriate visual areas. It attempts to explain the first few hundred milliseconds of visual processing and “immediate recognition”. One of the key elements in the approach is the learning of a generic dictionary of shape-components from V2 to IT, which provides an invariant representation to task-specific categorization circuits in higher brain areas. This vocabulary of shape-tuned units is learned in an unsupervised manner from natural images, and constitutes a large and redundant set of image features with different complexities and invariances. This theory significantly extends an earlier approach by (Riesenhuber & Poggio, 1999) and builds upon several existing neurobiological models and conceptual proposals.First, I present evidence to show that the model can duplicate the tuning properties of neurons in various brain areas (e.g., V1, V4 and IT). In particular, the model agrees with data from V4 about the response of neurons to combinations of simple two-bar stimuli (Reynolds et al, 1999) (within the receptive field of the S2 units) and some of the C2 units in the model show a tuning for boundary conformations which is consistent with recordings from V4 (Pasupathy & Connor, 2001). Second, I show that not only can the model duplicate the tuning properties of neurons in various brain areas when probed with artificial stimuli, but it can also handle the recognition of objects in the real-world, to the extent of competing with the best computer vision systems. Third, I describe a comparison between the performance of the model and the performance of human observers in a rapid animal vs. non-animal recognition task for which recognition is fast and cortical back-projections are likely to be inactive. Results indicate that the model predicts human performance extremely well when the delay between the stimulus and the mask is about 50 ms. This suggests that cortical back-projections may not play a significant role when the time interval is in this range, and the model may therefore provide a satisfactory description of the feedforward path.Taken together, the evidences suggest that we may have the skeleton of a successful theory of visual cortex. In addition, this may be the first time that a neurobiological model, faithful to the physiology and the anatomy of visual cortex, not only competes with some of the best computer vision systems thus providing a realistic alternative to engineered artificial vision systems, but also achieves performance close to that of humans in a categorization task involving complex natural images. / PhD thesis

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, aswell as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of (human) raters' visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithmwhich quantifies the vegetation cover was able to process 98% of the image data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%. Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance. A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust mo nitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed formthe foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

This thesis was conducted to provide an automated method for characterization of printed electronics. The work was built on a multi-axis milling machine. Further, the machine was modified by replacing the milling-tool with an installment utilizing electrical probing. Different measurement techniques, machine vision applications, and software solutions were evaluated and utilized. All the revolving functionalities of this project was then merged into a complete system, controlled by a graphical user interface. The resulting system was capable of autonomously characterize a given number of components on a printed sheet. The final version of the system is capable of finding the origin of the sheet by using machine vision and fiducial markers.

As an engineering student, the most natural way of summarizing this thesis project is by relating it to a mathematical equation. The solution to this equation is given, and it is in the form of a racking concept that enables the use of robots. The other side of the equation is however a bit more complex. This side contains several undefined variables, which can only be solved by delving into various theoretical fields and exploring unchartered depths of the creative space.The project’s main objective is to design a concept rack for Gestamp HardTech in Luleå, Sweden, for storage and in-house transport of the beams which are produced at the HardTech facility. The rack is meant to be loaded both into and out of by robots and should suit an as wide array of beams as possible. To determine the possibilities and limitations of the rack’s robot-user, several automation aspects are researched, centered on industrial robots and machine vision. The beams which are produced at the Gestamp HardTech Luleå production plant today are analyzed, whereby twelve of them are ultimately chosen for the rack’s design to be focused on. What follows this is a creative process consisting of a creative idea-generating phase, an evaluative phase focused on implementation of the ideas, and a refinement phase where the rack concept is finalized. The process includes various methods of idea generating, a great deal of sketching, physical testing of the concepts, and finally CAD-modeling. The result, named 4.0-Rack, is in the form of a modular rack-concept which balances the aspects of flexibility, by suiting ten of the reviewed beams, with a high packing-grade, providing a mean packing-grade of 83% in relation to the way the beams are currently packed.

abstract: The demand for miniaturized components with feature sizes as small as tens of microns and tolerances as small as 0.1 microns is on the rise in the fields of aerospace, electronics, optics and biomedical engineering. Micromilling has proven to be a process capable of generating the required accuracy for these features and is an alternative to various non-mechanical micro-manufacturing processes which are limited in terms of cost and productivity, especially at the micro-meso scale. The micromilling process is on the surface, a miniaturized version of conventional milling, hence inheriting its benefits. However, the reduction in scale by a few magnitudes makes the process peculiar and unique; and the macro-scale theories have failed to successfully explain the micromilling process and its machining parameters. One such characteristic is the unpredictable nature of tool wear and breakage. There is a large cost benefit that can be realized by improving tool life. Workpiece rejection can also be reduced by successfully monitoring the condition of the tool to avoid issues. Many researchers have developed Tool Condition Monitoring and Tool Wear Modeling systems to address the issue of tool wear, and to obtain new knowledge. In this research, a tool wear modeling effort is undertaken with a new approach. A new tool wear signature is used for real-time data collection and modeling of tool wear. A theoretical correlation between the number of metal chips produced during machining and the condition of the tool is introduced. Experimentally, it is found that the number of chips produced drops with respect to the feedrate of the cutting process i.e. when the uncut chip thickness is below the theoretical minimum chip thickness. / Dissertation/Thesis / Masters Thesis Engineering 2015

O sistema óptico baseado em Visão Computacional, consiste em dispositivos de geração, aquisição e processamento das imagens da incidência de um feixe laser sobre a superfície de um escoamento e reflexão sobre uma tela horizontal. Com função de medição da turbulência na superfície do fluxo, os dispositivos de geração e aquisição de imagens foram condicionados sobre um tanque de produção hidrodinâmica de turbulência, acionado por grades oscilantes. Um software, com interface gráfica, foi desenvolvido para processamento das imagens e obtenção de dados geométricos do escoamento. Com até 30 quadros por segundo é possível visualizar a oscilação turbulenta e também as superfícies 3D, equivalentes ao escoamento real, geradas numa malha de diferenças finitas. Obtêm-se velocidades verticais, ampliações superficiais e velocidades angulares, entre outros parâmetros, em diversas situações de turbulência. No mesmo tanque foram procedidas, previamente, medidas de concentração de oxigênio dissolvido segundo uma técnica que permite determinar o coeficiente de reaeração K2. Em modelo gráfico foram reunidos dados de turbulência e coeficientes K2 de forma a possibilitar a previsão desse coeficiente em escoamentos naturais, com aplicação na estimativa da capacidade de autodepuração nos corpos d\'água receptores de efluentes, que sofrem rebaixamento do nível de oxigênio. / The optical system based on machine vision consists on generation, acquisition and processing devices of the images of a laser beam incidence on a flow surface and reflection on a horizontal screen. To measure the turbulence in the surface flow, the generation and acquisition of images devices were conditioned on a tank of hydrodynamic turbulence production by oscillating grids. Software, with graphic interface, was developed for processing the images and obtaining geometric data of the flow. With up to 30 pictures per second it is possible to visualize the turbulent oscillation and also the 3D surfaces, equivalent to the real flow, generated in a mesh of finite differences. Vertical velocities, surface enlargements and angular velocities are obtained, among other parameters, in several turbulence situations. In the same tank were proceeded, previously, measures of concentration of dissolved oxygen according to a technique that allows to determine the reaeration coefficient K2. Turbulence data and coefficients K2 were gathered in a graphic model to make possible the forecast of this coefficient in natural flows, with application on the estimation of the natural depuration capability in the receiving water bodies of inflows, that suffer lowering of the oxygen level.

This study explored the development of a stationary robotic strawberry harvester that was combined with a movable bench system as part of the development of an industrially production system for a strawberry in a plant factory. At first the difficulty of approaching target fruit was investigated using table-top plants cultured in a greenhouse. Then the maximum force needed to separate fruit from the peduncle was measured. Based on these results, an end-effector was designed with three unique functions; (1) suction cup was vibrated to minimize the influence of the adjoining fruits at the time of approach; (2) compressed air was blown toward the adjoining fruits to force them away from the target fruit; (3) peduncle was removed with the motion of tilting and pulling the target fruit. Next, an optical system to equip the machine with the ability to detect and determine the position and coloration of strawberry fruit was constructed. The position of the fruit was detected from below with a stereo-camera. The coloration measurement unit was set against the bed of the movable bench system at fruit level to capture images of target fruit. Considering the spectral reflectance characteristics of strawberry fruit, the coloration measurement unit was equipped with red, green, and white LEDs. Finally the stationary robot was tested in an experimental harvesting system in which the robot was combined with a movable bench unit. In the experiment system, the stationary robot enabled highly stable harvesting operation. / Kyoto University (京都大学) / 0048 / 新制・論文博士 / 博士(農学) / 乙第12528号 / 論農博第2747号 / 新制||農||988(附属図書館) / 学位論文||H23||N4584(農学部図書室) / 28350 / (主査)教授 近藤 直, 教授 清水 浩, 准教授 飯田 訓久 / 学位規則第4条第2項該当

Abstract The colours of objects perceived by a colour camera are dependent on the illumination conditions. For example, when the prevailing illumination condition does not correspond to the one used in the white balancing of the camera, the object colours can change their appearance due to the lack of colour constancy capabilities. Many methods for colour constancy have been suggested but so far their performance has been inadequate. Faces are common and important objects encountered in many applications. Therefore, this thesis is dedicated to studying face colours and their robust use under real world illumination conditions. The main thesis statement is "knowledge about an object's colour, like skin colour changes under different illumination conditions, can be used to develop more robust techniques against illumination changes". Many face databases exist, and in some cases they contain colour images and even videos. However, from the point of view of this thesis these databases have several limitations: unavailability of spectral data related to image acquisition, undefined illumination conditions of the acquisition, and if illumination change is present it often means only change in illumination direction. To overcome these limitations, two databases, a Physics-Based Face Database and a Face Video Database were created. In addition to the images, the Physics-Based Face Database consists of spectral data part including skin reflectances, channel responsivities of the camera and spectral power distribution of the illumination. The images of faces are taken under four known light sources with different white balancing illumination conditions for over 100 persons. In addition to videos, the Face Video Database has spectral reflectances of skin for selected persons and images taken with the same measurement arrangement as in the Physics-Based Face Database. The images and videos are taken with several cameras. The databases were used to gather information about skin chromaticities and to provide test material. The skin RGB from images were converted to different colour spaces and the result showed that the normalized colour coordinate was among the most usable colour spaces for skin chromaticity modelling. None of the colour spaces could eliminate the colour shifts in chromaticity. The obtained chromaticity constraint can be implemented as an adaptive skin colour modelling part of face tracking algorithms, like histogram backprojection or mean shift. The performances of these adaptive algorithms were superior compared to those using a fixed skin colour model or model adaptation based on spatial pixel selection. Of course, there are cases when the colour cue is not enough alone and use of other cues like motion or edge data would improve the result. It was also demonstrated that the skin colour model can be used to segment faces and the segmentation results depend on the background due to the method used. Also an application for colour correction using principal component analysis and a simplified dichromatic reflection model was shown to improve colour quality of seriously clipped images. The results of tracking, segmentation and colour correction experiments using the collected data validate the thesis statement.

The industrial testing phase of graphical user interfaces and the behaviour of screens, is still involving manual tests with human interaction. This type of testing is particularly difficult and time consuming to manually perform, due to time sensitive messages and information used within these interfaces. This thesis address this issue by introducing an approach to automate this process by utilizing high grade machine vision cameras and existing algorithm implementations from OpenCV 3.2.0. By knowing the expected graphical representation in advance, a comparison between the actual outcome and this expectation can be evaluated by applying image processing algorithms. It is found that this approach presents an Equal Error Rate of 6% while still maintaining a satisfactory time performance, in relation to the timeframe requirement of these time sensitive messages. Accuracy and time performance is profoundly affected by hardware equipment, partially due to the immense amount of image processing involved.