Downtime reduction analysis of the Australia Post flat mail optical character reader

Machine downtime, whether planned or unplanned, is intuitively costly to manufacturing organisations, but is often very difficult to quantify. The available literature showed that costing processes are rarely undertaken within manufacturing organisations. Where cost analyses have been undertaken, they generally have only valued a small proportion of the affected costs, leading to an overly conservative estimate. This thesis aimed to develop a cost of downtime model, with particular emphasis on the application of the model to Australia Post’s Flat Mail Optical Character Reader (FMOCR). The costing analysis determined a cost of downtime of $5,700,000 per annum, or an average cost of $138 per operational hour. The second section of this work focused on the use of the cost of downtime to objectively determine areas of opportunity for cost reduction on the FMOCR. This was the first time within Post that maintenance costs were considered along side of downtime for determining machine performance. Because of this, the results of the analysis revealed areas which have historically not been targeted for cost reduction. Further exploratory work was undertaken on the Flats Lift Module (FLM) and Auto Induction Station (AIS) Deceleration Belts through the comparison of the results against two additional FMOCR analysis programs. This research has demonstrated the development of a methodical and quantifiable cost of downtime for the FMOCR. This has been the first time that Post has endeavoured to examine the cost of downtime. It is also one of the very few methodologies for valuing downtime costs that has been proposed in literature. The work undertaken has also demonstrated how the cost of downtime can be incorporated into machine performance analysis with specific application to identifying high costs modules. The outcome of this report has both been the methodology for costing downtime, as well as a list of areas for cost reduction. In doing so, this thesis has outlined the two key deliverables presented at the outset of the research.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Obstacle detection using optical flow

Motion has been examined in biology to be a critical component for obstacle avoidance and navigation. In particular, optical flow is a powerful motion cue that has been exploited in many biological systems for survival. In this paper, we investigate an obstacle detection system that uses optical flow to obtain range information to objects. Our experimental results demonstrate that optical flow is capable of providing good obstacle information but has obvious failure modes. We acknowledge that our optical flow system has certain disadvantages and cannot be solely used for navigation. Instead, we believe that optical flow is a critical visual subsystem used when moving at reason- able speeds. When combined with other visual subsystems, considerable synergy can result.

The strength and failure of silica optical fibers

The mechanical strength and failure behavior of conventional and microstructured silica optical fibers was investigated using a tensile test and fracture mechanics and numerical analyses. The effect of polymer coating on failure behavior was also studied. The results indicate that all these fibers fail in a brittle manner and failure normally starts from fiber surfaces. The failure loads observed in coated fibers are higher than those in bare fibers. The introduction of air holes reduces fiber strength and their geometrical arrangements have a remarkable effect on stress distribution in the longitudinal direction. These results are potentially useful for the design, fabrication and evaluation of optical fibers for a wide range of applications.

Virtual force feedback teleoperation of the InsectBot using optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator’s joystick to facilitate collision free teleoperation. Optical flow is measured by a pair of wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. Experimental results are provided on the InsectBot holonomic vehicle platform.

A new framework for force feedback teleoperation of robotic vehicles based on optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator's joystick to facilitate collision free teleoperation. Optic flow is measured by wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. The coupling between optical flow (velocity) and force is modelled as an impedance - in this case an optical impedance. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. The paper focuses on applications to aerial robotics vehicles, however, the ideas apply directly to other force actuated vehicles such as submersibles or space vehicles, and the authors believe the approach has potential for control of terrestrial vehicles and even teleoperation of manipulators. Experimental results are provided for a simulated aerial robot in a virtual environment controlled by a haptic joystick.

Perceptions of daylight quality delivered by light transport systems

Light Transport Systems (LTS) (e.g lightpipes, fibre optics) can illuminate core areas within buildings with great potential for energy savings. However, they do not provide a clear connection to the outside like windows do, and their effects on people’s physiological and psychological health are not well understood. Furthermore, how people perceive LTS affects users’ acceptance of the device and its performance. The purpose of this research is to understand how occupants perceive and experience spaces illuminated by LTS. Two case studies of commercial buildings with LTS, located in Brisbane, Australia are assessed by qualitative (focus group interviews) and quantitative (measurement of daylight illuminances and luminance) methods. The data from interviews with occupants provide useful insight into the aspects of LTS design that are most relevant to positive perception of the luminous environment. Luminance measurements of the occupied spaces support the perception of the LTS reported by occupants: designs that create high contrast luminous environments are more likely to be perceived negatively.

Group segmentation during object tracking using optical flow discontinuities

Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people wearing dark suits. In this paper, we propose a novel technique to segment groups and resolve occlusions using optical flow discontinuities. We demonstrate that the ratio of continuous to discontinuous pixels within a region can be used to locate the overlapping edges, and incorporate this into an object tracking framework. Results on a portion of the ETISEO database show that the proposed algorithm results in improved tracking performance overall, and improved tracking within occlusions.

Fixed-wing attitude estimation using temporal tracking of the horizon and optical flow

In this paper, a method has been developed for estimating pitch angle, roll angle and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front-end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an Extended Kalman Filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42◦ and 0.71◦ respectively when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79◦ and 1.75◦ respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front-end is also demonstrated.

Textures of optical flow for real-time anomaly detection in crowds

Automated visual surveillance of crowds is a rapidly growing area of research. In this paper we focus on motion representation for the purpose of abnormality detection in crowded scenes. We propose a novel visual representation called textures of optical flow. The proposed representation measures the uniformity of a flow field in order to detect anomalous objects such as bicycles, vehicles and skateboarders; and can be combined with spatial information to detect other forms of abnormality. We demonstrate that the proposed approach outperforms state-of-the-art anomaly detection algorithms on a large, publicly-available dataset.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Optical non-destructive evaluation of articular cartilage integrity : a review

This paper reviews the current status of the application of optical non-destructive methods, particularly infrared (IR) and near infrared (NIR), in the evaluation of the physiological integrity of articular cartilage. It is concluded that a significant amount of work is still required in order to achieve specificity and clinical applicability of these methods in the assessment and treatment of dysfunctional articular joints.