Vol. 14 (2005):
Abstracts of Papers
Zhang Y., Sim T., Tan C.L.:
Generating personalized anatomy-based 3D facial models
from scanned data.
MGV vol. 14, no. 1, 2005, pp. 3-28.
This paper presents a new method for reconstructing animatable,
anatomy-based human facial models from scanned range data. Our method
adapts a prototype model that is suitable for physically-based
animation to the geometry of a specific person's face with minimal
user intervention. The prototype model has a known topology
and incorporates a multi-layer structure of the skin, muscles,
and skull. Based on a series of measurements between a subset
of anthropometric landmarks specified on the prototype model
and the scanned surface, an automated global alignment adapts
the size, position, and orientation of the prototype model
to align it with the scanned surface. In the skin layer adaptation,
the generic skin mesh is represented as a dynamic deformable model
which is subjected to internal force stemming from the elastic
properties of the surface and external forces generated by the scanned
data points and features. We automatically deform the underlying
muscle layer consisting of three types of muscle models. A set
of automatically generated skull feature points is then transformed
based on the deformed external skin and muscle layers. The new
positions of these feature points are used to drive volume
morphing applied to the skull template for skull fitting.
With the adapted multi-layer anatomical structure, the reconstructed
model not only resembles the shape of the individual's face but can
also be animated instantly using the muscle and jaw parameters.
Key words: face reconstruction, facial animation,
anatomy-based model, multi-layer skin/muscle/skull structure,
scanned data, deformable model.
El-Bakry H.M., Zhao Q.:
Speeding-up normalized neural networks for face/object
MGV vol. 14, no. 1, 2005, pp. 29-59.
Finding an object or a face in an input image is a search problem
in the spatial domain. Neural networks have shown good results
in detecting a certain face/object in a given image. In this paper,
faster neural networks for face/object detection are presented.
Such networks are designed based on cross correlation in the frequency
domain between the input image and the input weights of neural
networks. This approach is developed to reduce the computation steps
required by these faster neural networks for the search process.
The principle of divide and conquer strategy is applied through
image decomposition. Each image is divided into small-size
sub-images, and then each of them is tested separately using
a single faster neural network. Furthermore, the fastest face/object
detection is achieved using parallel processing techniques to test
the resulting sub-images simultaneously using the same number
of faster neural networks. In contrast to using faster neural
networks only, the speed-up ratio is increased with the size
of the input image when using faster neural networks and image
decomposition. Moreover, the problem of local subimage
normalization in the frequency domain is solved. The effect
of image normalization on the speed-up ratio for face/object
detection is discussed. Simulation results show that local
subimage normalization through weight normalization is faster than
subimage normalization in the spatial domain. The overall speed-up
ratio of the detection process is increased as the normalization
of weights is carried out off line.
Key words: fast face/object detection,
neural networks, cross correlation, image normalization,
Zaqout I., Zainuddin R., Baba S.:
Pixel-based skin color detection technique.
MGV vol. 14, no. 1, 2005, pp. 61-70.
One of the simplest features used for the human face detection
problem is the skin color information. A simple and relatively
efficient histogram-based algorithm to segment skin pixels from
a complex background is presented. The histogram-based algorithm
used here is referred to as the lookup table (LUT) and is adopted
to identify those intervals which may fall in the skin locus plane.
For that purpose, a total of 306,401 skin samples are manually
collected from RGB color images to calculate three lookup tables
based on the relationship between each single pair of the three
components (R, G, B). To estimate the skin locus boundary, a skin
classifier box is created by integration of the proposed three
heuristic rules based on how often each RGB pixel-relationship
falls into its interval.
Key words: skin segmentation,
histogram-based approach, lookup table, heuristic rules,
Ogiela M.R., Tadeusiewicz R.:
Picture languages in machine understanding of medical
MGV vol. 14, no. 1, 2005, pp. 71-82.
This paper presents theoretical fundamentals and application
of context-free and graph languages for cognitive analysis of selected
medical visualization. It shows new opportunities for applying these
methods of automatic understanding of semantic contents of images
in intelligent medical information systems. A successful extraction
of the crucial semantic content of medical image may contribute
considerably to the creation of new intelligent cognitive systems,
or medical computer vision systems. Thanks to the new idea of cognitive
resonance between a stream of the data extracted from the image using
linguistic methods, and expectations following from the language
representation of the medical knowledge, it is possible to understand
the subject-oriented content of the visual data. This article shows
that structural techniques of soft-computing may be applied in automatic
classification and machine perception based on semantic pattern content
in order to determine the semantic meaning of the patterns.
Key words: structural pattern recognition,
image understanding, artificial intelligence, computer-aided diagnosis,
feature extraction, shape analysis.
Abdel-Qader I.M., Maddix M.E.:
Edge detection: wavelets versus conventional methods on DSP
MGV vol. 14, no. 1, 2005, pp. 83-101.
Edge detection is a
cornerstone in any computer, robotic or machine vision system.
Real time edge detection is a pre-process to many critical
applications, such as assembly line inspection and surveillance.
Wavelets-based algorithms are replacing traditional algorithms,
especially the Haar wavelet because of its simplicity. The Haar
algorithm uses a multilevel decomposition to produce image edges
corresponding to high frequency wavelet coefficients. In this
paper, a real time edge detection algorithm based on Haar is
analyzed and compared to conventional edge detectors. Other
implemented and compared algorithms are the traditional Prewitt
algorithm, and, from a newer generation, the Canny algorithm. The
real time implementation of all algorithms is accomplished using
TI TMS320C6711 card. In case of Haar, the multilevel decomposition
improves the results obtained with noisy images. The results show
that the Haar-based edge detector has a low execution time with
accurate edge results, and thus represents a suitable algorithm
for on-line vision system applications. Canny has produced the
thinnest edges, but is not suitable for real time processing using
the 6711, and falls short in edge results compared to the Haar
results. The wavelet-based algorithm has outperformed other edge
Key words: Haar Wavelets, edge detection, DSP processor.
Amplitude elimination for stereo image matching based
on the wavelet approach.
MGV vol. 14, no. 1, 2005, pp. 103-120.
Point-to-point correspondence is one of the most challenging
problems in stereo image matching. Correspondence or disparity
established between points of two images is the result of stereo
matching. The paper presents new point-to-point correspondence
algorithms based on wavelet analysis. Each image in the pair
is decomposed into an approximation, and details go through
the coarse to fine level. For the above decomposition,
multiresolution analysis is used. In the proposed approach,
a disparity is found in the wavelet transform space.
An extension and generalization of phase-based method is presented.
The classical Gabor's approach is extended to real wavelets.
Differences of amplitudes (grey levels) in images which frequently
appear in stereo pairs are eliminated. Invariance of the disparity
determination with respect to amplitude changes may be achieved
by choosing an appropriate pair of wavelet systems. The achieved
result is broader than the classical one, based on the Gabor wavelet
and the phase method. Numerical experiments with images have confirmed
this approach. Finally, three concepts (see Section 5) are presented
to analyse the problem of disparity determination globally.
Key words: stereo matching, point-to-point correspondence,
wavelet transform, amplitude elimination, disparity determination.
Foufou S., Garnier L.:
Obtaining implicit equations of supercyclides and definition
of elliptic supercyclides.
MGV vol. 14, no. 2, 2005, pp. 123-144.
The use of Dupin cyclides and supercyclides in CAGD applications
has been the subject of many publications in the last decade.
Dupin cyclides are low degree algebraic surfaces having both
parametric and implicit representations. In this paper, we aim to give
the necessary expansions to derive implicit equations of supercyclides
in the affine as well as in the projective space, starting from equations
of the Dupin cyclide and the transformation matrix. We introduce
a particular subfamily of supercyclides, called elliptic supercyclides,
and show how to use them for the blending of elliptic quadratic
primitives. We also show how one can convert an elliptic supercyclide
into a set of rational biquadratic Bézier patches.
Key words: Dupin cyclides, supercyclides,
projective and affine geometry.
Cheng B., Wang Y., Zheng N., Bian Z.:
Object based segmentation of video using variational
MGV vol. 14, no. 2, 2005, pp. 145-157.
The paper demonstrates a new approach to video segmentation which
retains some of the attractive features of existing methods and overcomes
some of their limitations. The video sequence is represented
as a spatio-temporal volume, and is segmented by an extension
of active contour model based on Mumford-Shah techniques.
The energy function minimization is similar to 3D interface evolution
with curvature-dependent speeds. The spatio-temporal volume need not
to be smoothed before processing because our method is not sensitive
to noise. Each object needs a closed interface, which is embedded
as a level set of a higher-dimensional functions, and is propagated
by solving a partial differential equation. The interface stops
in the vicinity of object boundaries, which are not necessarily
defined by the gradient and can be represented with complex topologies.
Finally, an experiment is given to show the effectiveness and robustness
of the method.
Key words: video sequence, segmentation,
Level set, Mumford-Shah functional.
Barsi A., Szirmay-Kalos L., Szécsi L.:
Image-based illumination on the GPU.
MGV vol. 14, no. 2, 2005, pp. 159-169.
In many computer graphics applications it is desirable to augment
virtual objects with high dynamic range images representing the real
environment. In order to provide an illusion that virtual objects
are part of the real scene, illumination of the environment should
be taken into account when rendering them. Proper calculation
of the illumination from an environment map may be extremely expensive
if we wish to account for occlusion, self shadowing and specular
materials. In this paper we present a method that performs all
the calculations on a per-frame basis, and is already real-time
on non-cutting-edge hardware.
Key words: HDRI, shadow, GPU, reflection.
Zaremba M.B., Palenichka R.M., Missaoui R.:
Multi-scale morphological modeling of a class
of structural texture.
MGV vol. 14, no. 2, 2005, pp. 171-199.
Consistent and time-efficient modeling of textures is important
both for realistic texture mapping in computer graphics and correct
texture segmentation in computer vision. A large class of natural
and artificial images is represented by the so-called structural
textures, which contain visibly repetitive patterns. The multi-scale
morphological modeling approach proposed in this paper explicitly
describes shape and intensity parameters of structural textures.
It is based on a cellular growth of a texture region by a sequential
morphological generation of structural texture cells starting
from a seed cell. Its main advantage is a concise shape representation
for structural texture cells in the form of piecewise linear skeletons.
Another advantage is a robust and computationally efficient estimation
of texture parameters. The cell parameter estimation is based
on the cell localization and adaptive segmentation using a multi-scale
matched filter. The experiments reported in the paper are related
to texture parameter estimation from synthetic and real textures
as well as structural texture synthesis based on the estimated parameters.
Key words: texture modeling, structural texture, local scale,
mathematical morphology, parameter estimation, binarization.
Abd Allah M.M.:
A novel approach for fingerprint classification system
based on new feature area search.
MGV vol. 14, no. 2, 2005, pp. 201-212.
The paper presents a new fast fingerprint classification method
based on direction patterns. The method is designed to be applicable
to today's embedded systems for fingerprint authentication, in which
small area sensors are employed (large enough to capture all the core
and delta points of a fingerprint). The proposed procedure consists
of four steps. First, ridge direction is determined at the pixel level.
Second, average orientation field flow is assessed within 8x8 blocks.
Then pattern matching is applied to determine presence of either
of three "feature areas". Finally, the target classes are identified
through a novel classification approach, called generally a pattern area.
We prove that the search of direction pattern in a specific area is able
to classify fingerprints clearly and quickly. With our algorithm,
the classification accuracy of 94% is achieved over 4000 images
in the NIST-4 database, slightly lower than the conventional approaches.
However, the classification speed has improved tremendously, up to about
10 times faster than the conventional singular point approaches
at the pixel level.
Key words: fingerprint classification, direction pattern,
Cowell J., Hussain F.:
Two template matching approaches to arabic, amharic
and latin isolated characters recognition.
MGV vol. 14, no. 1, 2005, pp. 213-232.
With the establishment of commercial OCR systems for Latin text,
recent research efforts have been directed at the design of recognition
systems for non-Latin scripts, such as Japanese, Cyrillic, Chinese, Hindi,
Tibetan, and in particular Arabic. The Unicode 4.0 standard supports
50 scripts that are used across the world, and many, such as Amharic
(Ethiopic), have attracted virtually no attention from researchers.
An extensive literature review reveals no papers which report on an OCR
system for Amharic. This paper describes a normalised technique which
can be used for recognition of isolated Arabic, Amharic and Latin characters.
Two approaches are considered for identifying the characters by comparing
them to a series of templates and using a signature template scheme.
The degrees of similarity between pairs of Amharic, Arabic and typical
Latin characters are presented in the confusion matrix, and the performance
of the two approaches is compared for each of these three character sets.
Key words: OCR, optical character recognition,
confusion matrix, fonts, script, Arabic, Amharic, Unicode, template matching.
El-Khamy S.E., Hadhoud M.M., Dessouky M.I., Salam B.M., Abd El-Samie F.E.:
An adaptive cubic convolution image interpolation approach.
MGV vol. 14, no. 3, 2005, pp. 235-258.
Key's (bicubic) image interpolation is one of the well-known,
state of the art image interpolation algorithms. In this paper,
we introduce an adaptive version of Key's interpolation algorithm.
The suggested adaptive algorithm is based on minimization
of the squared estimation error at each pixel in the interpolated image.
Thus, the overall mean square error (MSE) in the entire image
is minimized. The suggested algorithm takes into consideration
the low resolution (LR) image degradation model. The Key's formula
comprises two controling parameters. A study of the effect of optimizing
this formula with respect to the separated or combined parameters
is presented. The optimum values of the parameters are estimated
iteratively at each pixel. The performance of the suggested approach
is tested in the presence of noise with different levels and is compared
to the traditional warped distance interpolation technique.
A comparison of the suggested algorithm performance with other different
interpolation techniques used in the commercial ACDSee Software
is presented. The computational complexity of the suggested algorithm
is also studied in the paper. The obtained results ensure the superiority
of the suggested adaptive interpolation algorithm as compared
to the traditional algorithms from both of the MSE and edge preservation
points of view. As the results imply, the computation time
of the suggested algorithm is moderate.
Islam M.S., Sluzek A., Zhu L.:
Detecting and matching interest points in relative scale.
MGV vol. 14, no. 3, 2005, pp. 259-283.
The same object seen in two different images can be geometrically
and photometrically transformed. In this paper, a method of interest
point detection and matching is described for the same object
in different images. One of the main considerations is the change
in the object scale. In this method, a reference scale is assigned
to a particular instance of the object, and the change of scale
is represented by a relative scale. Then, Harris' relative scale
method is used for interest point detection. This method is robust
to linear geometric transformations. A heuristic method for threshold
selection is also described for robustness to intensity changes
in a cluttered environment with partial occlusions. The repeatability
rate of interest points for this method is higher then that
for the existing methods. For the matching process, a local invariant
descriptor is computed in the relative scale for each of the detected
interest points. A hashing technique is applied to find the matches
efficiently. The matching method enables finding a good number of correct
matches for different types of transformations in a cluttered environment
and one with partial occlusions. The proposed single scale detection
and matching method could be effectively used for many practical
applications, where the relative scale of the object can be predicted
Key words: relative scale, interest point,
local invariant descriptor, repeatability rate, moment invariant,
information content, multidimensional indexing.
Koprowski R., Wrobel Z.:
Automatic segmentation of biological cell structures
based on conditional opening and closing.
MGV vol. 14, no. 3, 2005, pp. 285-307.
In this work we present an innovative algorithm for the automatic
segmentation of biological cell structures based on two morphological
operations - conditional opening or conditional closing.
The operations do not have all the properties of classic erosion
and dilation operations, in particular the properties of opening
and closing. The metrological properties of the devised algorithm
are presented, with an emphasis on measurement errors that result
from the method used for the operation parameter selection.
Sensitivity of the algorithm to additive noise of Gaussian
distribution is studied, taking into special consideration
the microscopic images obtained from the examination of biological
cell structures. We also show the convergence of the devised
algorithm and its sensitivity to the quality of image binarization.
Some examples of segmentation of biological cell structure images
obtained from implementations of the algorithm, both in the Matlab
application with the Image Processing Toolbox and in Delphi, are shown.
Pattern recognition based on homology theory.
MGV vol. 14, no. 3, 2005, pp. 309-324.
This paper describes a method for comparing and recognizing patterns
based on homology theory. We present algorithms and an exemplary application
to handwritten letter recognition but the proposed idea can be easily
used to recognize patterns in any dimension.
Key words: homology algorithm, size function,
handwritten letter recognition.
Hussain M., Okada Y.:
LOD modelling of polygonal models.
MGV vol. 14, no. 3, 2005, pp. 325-343.
An automatic edge-collapse based simplification method has been proposed
for decimation of polygonal models and generating their LODs (Levels
of detail). The measure of geometric fidelity employed is motivated
by the normal space deviation of a polygonal model arising during
its decimation process and forces the algorithm to minimize the normal
space deviation. In spite of the global nature of the evaluation
of geometric deviation, the algorithm is memory efficient and involves
less execution time then the state-of-the art simplification algorithms.
This automatically prevents the creation of folds and automatically
preserves visually important features of the model even at low levels
of detail. LODs generated by our method compare favorably with those
produced by the standard QEM-based algorithm QSlim in terms of the mean
and maximum geometric errors, whereas its performance in preserving
normal space of the original model is better than that of QSlim.
Key words: triangular meshes, surface simplification,
level of detail, edge-collapse, shape approximation, multiresolution
New Books Notes
MGV vol. 14, no. 3, 2005, p. 345.
[A. Korzynska, M. Przytulska:
Przetwarzanie obrazˇw - Cwiczenia.
(Image Processing - Exercises, in Polish).
Published by PJWSTK, Warsaw 2005.]
Hernández Hoyos M., Orkisz M., Douek P.C., Magnin I.E.:
Assessment of carotid artery stenoses in 3D
contrast-enhanced magnetic resonance angiography, based on improved
generation of the centerline.
MGV vol. 14, no. 4, 2005, pp. 349-378.
A method is proposed for generation of the centerline of 3D tubular
shapes using an extensible-skeleton model. Starting from
a user-selected point, the skeleton grown by iteratively adding
subsequent centerline points within a prediction-estimation scheme
controlled by a multi-scale analysis of the image moments.
The location of the next point is predicted according the local
orientation of the tubular structure. The coordinates of the predicted
point are corrected under the influence of image forces and of prior
model shape constraints. The extraction of artery centerlines
from magnetic resonance angiography (MRA) images is described.
The goal is a quantitative assessment of arterial stenoses based
on cross-sectional diameters and areas of the vessel contours
in the planes locally perpendicular to the centerline. For this
purpose, iso-contours extraction based on an adaptive local
iso-value have been implemented. The robustness and accuracy
of the method have been demonstrated on MRA data on 5 reference
phantoms and on 17 patients' carotid arteries. 97% of the centerlines
were exploitable in the carotid arteries (100% in the phantoms).
On average, the centerlines were extracted within 1 second,
and the whole quantification process took less than 1 minute per artery, including interaction and display. The Mean difference (±
standard deviation) between stenosis percentages, semi-automatically
measured and visually estimated by radiologists, was 0.23% ± 7.89%.
The reproducibility of the semi-automatic method was significantly
Key words: 3D centerline, active model,
3D moments, angiography.
Jankó Z., Kós G., Chetverikov D.:
Creating entirely textured 3D models of real objects using
MGV vol. 14, no. 4, 2005, pp. 379-398.
We present a novel method to create entirely textured 3D models
of real objects by combiningpartial texture mappings using surface
flattening (surface parametrisation). Texturing a 3D model
is not trivial. Texture mappings can be obtained from optical
images, but usually one imageis not sufficient to show the whole
object; multiple images are required to cover the surface entirely.
Merging partial texture mappings in 3D is difficult. Surface flattening converts a 3D mesh into 2D space preserving its structure. Transforming optical images to flattening-based texture maps allows
them to be merged based onthe structure of the mesh. In this paper
we describe a novel method for merging texture mappings using flattening
and show its results on synthetic and real data.
Key words: 3D modelling, texturemapping, flattening,
Maskey M., Newman T.S.:
Cumulus cloud synthetic rendering techniques and their
MGV vol. 14, no. 4, 2005, pp. 399-425.
Three new techniques for synthesizing realistic renderings of cumulus
clouds are introducedand evaluated. The techniques utilize variations
of the Perlin Noise and Koch fractals to achieve a reasonable
cloud-like shape and texture. To evaluate the quality of renderings
produced by the techniques, three classes of texture features
are considered using cluster quality measures. Rendering quality
is also evaluated versus real images using shape and texture features.
Key words: Perlin noise, Koch curve, volume rendering,
fractals, texture, rendering quality, content-based image retrieval.
Rahman M., Kaneda K., Harada K.:
A new topology-based watermarking method for layered 3D
triangular mesh models.
MGV vol. 14, no. 4, 2005, pp. 427-439.
- A new topology-based watermarking method is proposed to embedi
nformation in objects with layered 3D triangular meshes such as those
reconstructed from CT or MRI data. The main idea of the methodis
to compare the heights of the vertices of a triangle lying in the same
layer. A watermark message is converted into a binary bit sequence,
and then embedded into the model in such a way that the first vertex
of a triangle in the upper level carries information 1, and the first
vertex of a triangle in the lower level carries information 0. For experimental purposes, a watermark message is embedded in a mouse
embryo model. It is robust against translation, rotation, re-sectioning,
local deformation and scaling. It lefts some artifacts after
re-arrangement of local or global numbering. It is useful for shape
sensitive 3D geometric models.
Key words: watermarking, layered 3D triangular mesh model,
topology based embedding, computer graphics.
Yang L., Sahli H., Hào D.N.:
A variational approach to 3D line orientation estimation
MGV vol. 14, no. 4, 2005, pp. 441-453.
A variational approach to estimating 3D line orientation from motion
is presented. A 2D motion constraint on 3D lines regularized
by a quadratic term is used to set up an objective functional.
From its associated Euler-Lagrange equations, we develop a vector-valued
diffusion model, with a reaction term based on the 2D motion constraint.
Three separate diffusion processes, corresponding to each component
of the 3D line orientation, are coupled with each other through
the reaction term and evolve simultaneously. Each 3D line orientation
is estimated separately. The regularization parameter is estimated
by an L-curve, which provides a better estimation. Experimental
results from image sequences indicate stability and accuracy
of the approach.
Key words: line orientation, motion,
variational approach, vector-valued reaction diffusion, L-curve.
Geometrical Wavelets and their Generalizations in Digital
Image Coding and Processing.
MGV vol. 14, no. 4, 2005, p. 455.
- Reviewers' index
- Authors' index
- Contents of volume 14, 2005
Maintained by Zenon Kulpa
Last updated Nov 28, 2006