2,462 research outputs found
Investigation of a new method for improving image resolution for camera tracking applications
Camera based systems have been a preferred choice in many motion tracking applications due to the ease of installation and the ability to work in unprepared environments. The concept of these systems is based on extracting image information (colour and shape properties) to detect the object location. However, the resolution of the image and the camera field-of- view (FOV) are two main factors that can restrict the tracking applications for which these systems can be used. Resolution can be addressed partially by using higher resolution cameras but this may not always be possible or cost effective.
This research paper investigates a new method utilising averaging of offset images to improve the effective resolution using a standard camera. The initial results show that the minimum detectable position change of a tracked object could be improved by up to 4 times
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Virtual viewpoint three-dimensional panorama
Conventional panoramic images are known to provide for an enhanced field of view in which the scene
always has a fixed appearance. The idea presented in this paper focuses on the use of the concept of virtual
viewpoint creation to generate different panoramic images of the same scene with three-dimensional
component. Three-dimensional effect in a resultant panorama is realized by superimposing a stereo-pair of
panoramic images
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Microscopy with ultraviolet surface excitation for rapid slide-free histology.
Histologic examination of tissues is central to the diagnosis and management of neoplasms and many other diseases, and is a foundational technique for preclinical and basic research. However, commonly used bright-field microscopy requires prior preparation of micrometre-thick tissue sections mounted on glass slides, a process that can require hours or days, that contributes to cost, and that delays access to critical information. Here, we introduce a simple, non-destructive slide-free technique that within minutes provides high-resolution diagnostic histological images resembling those obtained from conventional haematoxylin-and-eosin-histology. The approach, which we named microscopy with ultraviolet surface excitation (MUSE), can also generate shape and colour-contrast information. MUSE relies on ~280-nm ultraviolet light to restrict the excitation of conventional fluorescent stains to tissue surfaces, and it has no significant effects on downstream molecular assays (including fluorescence in situ hybridization and RNA-seq). MUSE promises to improve the speed and efficiency of patient care in both state-of-the-art and low-resource settings, and to provide opportunities for rapid histology in research
Image analysis of sports events
Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major de Automação). Faculdade de Engenharia. Universidade do Porto. 200
Digital forensic techniques for the reverse engineering of image acquisition chains
In recent years a number of new methods have been developed to detect image forgery. Most forensic techniques use footprints left on images to predict the history of the images. The images, however, sometimes could have gone through a series of processing and modification through their lifetime. It is therefore difficult to detect image tampering as the footprints could be distorted or removed over a complex chain of operations. In this research we propose digital forensic techniques that allow us to reverse engineer and determine history of images that have gone through chains of image acquisition and reproduction.
This thesis presents two different approaches to address the problem. In the first part we propose a novel theoretical framework for the reverse engineering of signal acquisition chains. Based on a simplified chain model, we describe how signals have gone in the chains at different stages using the theory of sampling signals with finite rate of innovation. Under particular conditions, our technique allows to detect whether a given signal has been reacquired through the chain. It also makes possible to predict corresponding important parameters of the chain using acquisition-reconstruction artefacts left on the signal.
The second part of the thesis presents our new algorithm for image recapture detection based on edge blurriness. Two overcomplete dictionaries are trained using the K-SVD approach to learn distinctive blurring patterns from sets of single captured and recaptured images. An SVM classifier is then built using dictionary approximation errors and the mean edge spread width from the training images. The algorithm, which requires no user intervention, was tested on a database that included more than 2500 high quality recaptured images. Our results show that our method achieves a performance rate that exceeds 99% for recaptured images and 94% for single captured images.Open Acces
3D Spatial Sensor
This project entitled 3D spatial sensor which is a sensor that is designed for sensing touch
coordinates in 3 dimensions for 3D application such as 3Dmodeling andhumancomputer interface.
The main idea of this project is to develop 3D sensor that can be used by everybody with minimal
learnability and cost.
3D sensor is important to this world because our real world is a 3 dimensions world hence
our interaction with computer has to be in 3 dimensions so that the real data can be inputted into the
computer for further processing. However, many of the sensors for human computer interaction is
limited to 2 dimensions such as keyboard, mouse and touch screen device, hence the real interaction
between human and computer is limited by those devices.
In this project, the development of 3D spatial sensors will be based on a novel method which
make used of 2 cameras for 2 different spatial planes and a computer to calculate and derived the
3Dcoordinates from boththe image frames from the 2 cameras. Froma single touch 3D spatial
sensor, additional efforts and resources will be used to develop a multiple touch 3D spatial sensors.
Lastly, multiple touch 3D spatial sensors will be incorporate into different applications to
demonstrate the abilities of these sensors. Hopefully the development of this device can benefit
human and enhance the experience ofhuman computer interaction
Non-parametric Methods for Automatic Exposure Control, Radiometric Calibration and Dynamic Range Compression
Imaging systems are essential to a wide range of modern day
applications. With the continuous advancement in imaging systems,
there is an on-going need to adapt and improve the imaging
pipeline running inside the imaging systems.
In this thesis, methods are presented to improve the imaging
pipeline of digital cameras. Here we present three methods to
improve important phases of the imaging process, which are (i)
``Automatic exposure adjustment'' (ii) ``Radiometric
calibration'' (iii) ''High dynamic range compression''. These
contributions touch the initial, intermediate and final stages of
imaging pipeline of digital cameras.
For exposure control, we propose two methods. The first makes use
of CCD-based equations to formulate the exposure control problem.
To estimate the exposure time, an initial image was acquired for
each wavelength channel to which contrast adjustment techniques
were applied. This helps to recover a reference cumulative
distribution function of image brightness at each channel. The
second method proposed for automatic exposure control is an
iterative method applicable for a broad range of imaging systems.
It uses spectral sensitivity functions such as the photopic
response functions for the generation of a spectral power image
of the captured scene. A target image is then generated using the
spectral power image by applying histogram equalization. The
exposure time is hence calculated iteratively by minimizing the
squared difference between target and the current spectral power
image. Here we further analyze the method by performing its
stability and controllability analysis using a state space
representation used in control theory. The applicability of the
proposed method for exposure time calculation was shown on real
world scenes using cameras with varying architectures.
Radiometric calibration is the estimate of the non-linear mapping
of the input radiance map to the output brightness values. The
radiometric mapping is represented by the camera response
function with which the radiance map of the scene is estimated.
Our radiometric calibration method employs an L1 cost function by
taking advantage of Weisfeld optimization scheme. The proposed
calibration works with multiple input images of the scene with
varying exposure. It can also perform calibration using a single
input with few constraints. The proposed method outperforms,
quantitatively and qualitatively, various alternative methods
found in the literature of radiometric calibration.
Finally, to realistically represent the estimated radiance maps
on low dynamic range display (LDR) devices, we propose a method
for dynamic range compression. Radiance maps generally have
higher dynamic range (HDR) as compared to the widely used display
devices. Thus, for display purposes, dynamic range compression is
required on HDR images. Our proposed method generates few LDR
images from the HDR radiance map by clipping its values at
different exposures. Using contrast information of each LDR
image generated, the method uses an energy minimization approach
to estimate the probability map of each LDR image. These
probability maps are then used as label set to form final
compressed dynamic range image for the display device. The
results of our method were compared qualitatively and
quantitatively with those produced by widely cited and
professionally used methods
Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels
The detection of pest infestation is an important aspect of forest management. In the case of the oak splendour beetle (Agrilus biguttatus) infestation, the affected oaks (Quercus sp.) show high levels of defoliation and altered canopy reflection signature. These critical features can be identified in high-resolution colour infrared (CIR) images of the tree crown and branches level captured by Unmanned Aerial Systems (UAS). In this study, we used a small UAS equipped with a compact digital camera which has been calibrated and modified to record not only the visual but also the near infrared reflection (NIR) of possibly infested oaks. The flight campaigns were realized in August 2013, covering two study sites which are located in a rural area in western Germany. Both locations represent small-scale, privately managed commercial forests in which oaks are economically valuable species. Our workflow includes the CIR/NIR image acquisition, mosaicking, georeferencing and pixel-based image enhancement followed by object-based image classification techniques. A modified Normalized Difference Vegetation Index (NDVImod) derived classification was used to distinguish between five vegetation health classes, i.e., infested, healthy or dead branches, other vegetation and canopy gaps. We achieved an overall Kappa Index of Agreement (KIA) of 0.81 and 0.77 for each study site, respectively. This approach offers a low-cost alternative to private forest owners who pursue a sustainable management strategy
The use of low cost virtual reality and digital technology to aid forensic scene interpretation and recording
© Cranfield University 2005. All rights reserved. No part of this publication may be
reproduced without the written permission of the copyright owner.Crime scenes are often short lived and the opportunities must not be lost in acquiring
sufficient information before the scene is disturbed. With the growth in information
technology (IT) in many other scientific fields, there are also substantial opportunities
for IT in the area of forensic science. The thesis sought to explore means by which IT
can assist and benefit the ways that forensic information can be illustrated and
elucidated in a logical manner. The central research hypothesis considers that through
the utilisation of low cost IT, the visual presentation of information will be of
significant benefit to forensic science in particular for the recoding of crime scenes and
its presentation in court.
The research hypothesis was addressed by first exploring the current crime scene
documentation techniques; their strengths and weaknesses, giving indication to the
possible niche that technology could occupy within forensic science. The underlying
principles of panoramic technology were examined, highlighting its ability to express
spatial information efficiently. Through literature review and case studies, the current
status of the technology within the forensic community and courtrooms was also
explored to gauge its possible acceptance as a forensic tool.
This led to the construction of a low cost semi-automated imaging system capable of
capturing the necessary images for the formation of a panorama. This provides the
ability to pan around; effectively placing the viewer at the crime scene. Evaluation and
analysis involving forensic personnel was performed to assess the capabilities and
effectiveness of the imaging system as a forensic tool. The imaging system was found
to enhance the repertoire of techniques available for crime scene documentation;
possessing sufficient capabilities and benefits to warrant its use within the area of forensics, thereby supporting the central hypothesis
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