13,429 research outputs found
Polarised light stress analysis and laser scatter imaging for non-contact inspection of heat seals in food trays
This paper introduces novel non-contact methods for detecting faults in heat seals of food packages. Two alternative imaging technologies are investigated; laser scatter imaging and polarised light stress images. After segmenting the seal area from the rest of the respective image, a classifier is trained to detect faults in different regions of the seal area using features extracted from the pixels in the respective region. A very large set of candidate features, based on statistical information relating to the colour and texture of each region, is first extracted. Then an adaptive boosting algorithm (AdaBoost) is used to automatically select the best features for discriminating faults from non-faults. With this approach, different features can be selected and optimised for the different imaging methods. In experiments we compare the performance of classifiers trained using features extracted from laser scatter images only, polarised light stress images only, and a combination of both image types. The results show that the polarised light and laser scatter classifiers achieved accuracies of 96\% and 90\%, respectively, while the combination of both sensors achieved an accuracy of 95\%. These figures suggest that both systems have potential for commercial development
Provably scale-covariant networks from oriented quasi quadrature measures in cascade
This article presents a continuous model for hierarchical networks based on a
combination of mathematically derived models of receptive fields and
biologically inspired computations. Based on a functional model of complex
cells in terms of an oriented quasi quadrature combination of first- and
second-order directional Gaussian derivatives, we couple such primitive
computations in cascade over combinatorial expansions over image orientations.
Scale-space properties of the computational primitives are analysed and it is
shown that the resulting representation allows for provable scale and rotation
covariance. A prototype application to texture analysis is developed and it is
demonstrated that a simplified mean-reduced representation of the resulting
QuasiQuadNet leads to promising experimental results on three texture datasets.Comment: 12 pages, 3 figures, 1 tabl
Visual detection of blemishes in potatoes using minimalist boosted classifiers
This paper introduces novel methods for detecting blemishes in potatoes using machine vision. After segmentation of the potato from the background, a pixel-wise classifier is trained to detect blemishes using features extracted from the image.
A very large set of candidate features, based on statistical information relating to the colour and texture of the region surrounding a given pixel, is first extracted.
Then an adaptive boosting algorithm (AdaBoost) is used to automatically select the best features for discriminating between blemishes and non-blemishes.
With this approach, different features can be selected for different potato varieties, while also handling the natural variation in fresh produce due to different seasons, lighting conditions, etc.
The results show that the method is able to build ``minimalist'' classifiers that optimise detection performance at low computational cost.
In experiments, blemish detectors were trained for both white and red potato varieties, achieving 89.6\% and 89.5\% accuracy, respectively
Edge Detection: A Collection of Pixel based Approach for Colored Images
The existing traditional edge detection algorithms process a single pixel on
an image at a time, thereby calculating a value which shows the edge magnitude
of the pixel and the edge orientation. Most of these existing algorithms
convert the coloured images into gray scale before detection of edges. However,
this process leads to inaccurate precision of recognized edges, thus producing
false and broken edges in the image. This paper presents a profile modelling
scheme for collection of pixels based on the step and ramp edges, with a view
to reducing the false and broken edges present in the image. The collection of
pixel scheme generated is used with the Vector Order Statistics to reduce the
imprecision of recognized edges when converting from coloured to gray scale
images. The Pratt Figure of Merit (PFOM) is used as a quantitative comparison
between the existing traditional edge detection algorithm and the developed
algorithm as a means of validation. The PFOM value obtained for the developed
algorithm is 0.8480, which showed an improvement over the existing traditional
edge detection algorithms.Comment: 5 Page
Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification
We present a method for automated segmentation of the vasculature in retinal
images. The method produces segmentations by classifying each image pixel as
vessel or non-vessel, based on the pixel's feature vector. Feature vectors are
composed of the pixel's intensity and continuous two-dimensional Morlet wavelet
transform responses taken at multiple scales. The Morlet wavelet is capable of
tuning to specific frequencies, thus allowing noise filtering and vessel
enhancement in a single step. We use a Bayesian classifier with
class-conditional probability density functions (likelihoods) described as
Gaussian mixtures, yielding a fast classification, while being able to model
complex decision surfaces and compare its performance with the linear minimum
squared error classifier. The probability distributions are estimated based on
a training set of labeled pixels obtained from manual segmentations. The
method's performance is evaluated on publicly available DRIVE and STARE
databases of manually labeled non-mydriatic images. On the DRIVE database, it
achieves an area under the receiver operating characteristic (ROC) curve of
0.9598, being slightly superior than that presented by the method of Staal et
al.Comment: 9 pages, 7 figures and 1 table. Accepted for publication in IEEE
Trans Med Imag; added copyright notic
Interactive real-time three-dimensional visualisation of virtual textiles
Virtual textile databases provide a cost-efficient alternative to the use of existing hardcover
sample catalogues. By taking advantage of the high performance features offered by the
latest generation of programmable graphics accelerator boards, it is possible to combine
photometric stereo methods with 3D visualisation methods to implement a virtual textile
database. In this thesis, we investigate and combine rotation invariant texture retrieval with
interactive visualisation techniques.
We use a 3D surface representation that is a generic data representation that allows us to
combine real-time interactive 3D visualisation methods with present day texture retrieval
methods. We begin by investigating the most suitable data format for the 3D surface
representation and identify relief-mapping combined with Bézier surfaces as the most
suitable 3D surface representations for our needs, and go on to describe how these
representation can be combined for real-time rendering. We then investigate ten different
methods of implementing rotation invariant texture retrieval using feature vectors. These
results show that first order statistics in the form of histogram data are very effective for
discriminating colour albedo information, while rotation invariant gradient maps are
effective for distinguishing between different types of micro-geometry using either first or
second order statistics.Engineering and physical Sciences Research (EPSRC
Distance Measures for Reduced Ordering Based Vector Filters
Reduced ordering based vector filters have proved successful in removing
long-tailed noise from color images while preserving edges and fine image
details. These filters commonly utilize variants of the Minkowski distance to
order the color vectors with the aim of distinguishing between noisy and
noise-free vectors. In this paper, we review various alternative distance
measures and evaluate their performance on a large and diverse set of images
using several effectiveness and efficiency criteria. The results demonstrate
that there are in fact strong alternatives to the popular Minkowski metrics
Geometric study of Lagrangian and Eulerian structures in turbulent channel flow
We report the detailed multi-scale and multi-directional geometric study of both evolving Lagrangian and instantaneous Eulerian structures in turbulent channel flow at low and moderate Reynolds numbers. The Lagrangian structures (material surfaces) are obtained by tracking the Lagrangian scalar field, and Eulerian structures are extracted from the swirling strength field at a time instant. The multi-scale and multi-directional geometric analysis, based on the mirror-extended curvelet transform, is developed to quantify the geometry, including the averaged inclination and sweep angles, of both structures at up to eight scales ranging from the half-height δ of the channel to several viscous length scales δ_ν. Here, the inclination angle is on the plane of the streamwise and wall-normal directions, and the sweep angle is on the plane of streamwise and spanwise directions. The results show that coherent quasi-streamwise structures in the near-wall region are composed of inclined objects with averaged inclination angle 35°–45°, averaged sweep angle 30°–40° and characteristic scale 20δ_ν, and 'curved legs' with averaged inclination angle 20°–30°, averaged sweep angle 15°–30° and length scale 5δ_ν–10δ_ν. The temporal evolution of Lagrangian structures shows increasing inclination and sweep angles with time, which may correspond to the lifting process of near-wall quasi-streamwise vortices. The large-scale structures that appear to be composed of a number of individual small-scale objects are detected using cross-correlations between Eulerian structures with large and small scales. These packets are located at the near-wall region with the typical height 0.25δ and may extend over 10δ in the streamwise direction in moderate-Reynolds-number, long channel flows. In addition, the effects of the Reynolds number and comparisons between Lagrangian and Eulerian structures are discussed
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