Abstract: In this work, we present a comparison between
different techniques of image compression. First, the image is
divided in blocks which are organized according to a certain scan.
Later, several compression techniques are applied, combined or
alone. Such techniques are: wavelets (Haar's basis), Karhunen-Loève
Transform, etc. Simulations show that the combined versions are the
best, with minor Mean Squared Error (MSE), and higher Peak Signal
to Noise Ratio (PSNR) and better image quality, even in the presence
of noise.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a level-sets approach to delineating three-dimensional brain tumors. Then we introduce a compression plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: In this article, biomechanical aspects of hen-s eggshell as a natural ceramic structure are studied. The images, taken by a scanning electron microscope (SEM), are used to investigate the microscopic aspects of the egg. It is observed that eggshell has a three-layered microstructure with different morphological and structural characteristics. Studies on the eggshell membrane (ESM) as a prosperous tissue suggest that it is placed to prevent the penetration of microorganisms into the egg. Finally, numerical models of the egg are presented to study the stress distribution and its deformation under different loading conditions. The effects of two different types of loading (hydrostatic and point loadings) on two different shell models (with constant and variable thicknesses) are investigated in detail.
Abstract: The paper aims to specify and build a system, a learning support in radiology-senology (breast radiology) dedicated to help assist junior radiologists-senologists in their radiologysenology- related activity based on experience of expert radiologistssenologists. This system is named SAFRS (i.e. system supporting the training of radiologists-senologists). It is based on the exploitation of radiologic-senologic images (primarily mammograms but also echographic images or MRI) and their related clinical files. The aim of such a system is to help breast cancer screening in education. In order to acquire this expert radiologist-senologist knowledge, we have used the CBR (case-based reasoning) approach. The SAFRS system will promote the evolution of teaching in radiology-senology by offering the “junior radiologist" trainees an advanced pedagogical product. It will permit a strengthening of knowledge together with a very elaborate presentation of results. At last, the know-how will derive from all these factors.
Abstract: One of the main limitations for the resolution of
optical instruments is the size of the sensor-s pixels. In this paper we
introduce a new sub pixel resolution algorithm to enhance the
resolution of images. This method is based on the analysis of multiimages
which are fast recorded during the fine relative motion of
image and pixel arrays of CCDs. It is shown that by applying this
method for a sample noise free image one will enhance the resolution
with 10-14 order of error.
Abstract: In this work we propose a novel Steganographic
method for hiding information within the spatial domain of the gray
scale image. The proposed approach works by dividing the cover into
blocks of equal sizes and then embeds the message in the edge of the
block depending on the number of ones in left four bits of the pixel.
The proposed approach is tested on a database consists of 100
different images. Experimental results, compared with other
methods, showed that the proposed approach hide more large
information and gave a good visual quality stego-image that can be
seen by human eyes.
Abstract: In this paper, we proposed the robust mobile object
detection method for light effect in the night street image block based
updating reference background model using block state analysis.
Experiment image is acquired sequence color video from steady
camera. When suddenly appeared artificial illumination, reference
background model update this information such as street light, sign
light. Generally natural illumination is change by temporal, but
artificial illumination is suddenly appearance. So in this paper for
exactly detect artificial illumination have 2 state process. First process
is compare difference between current image and reference
background by block based, it can know changed blocks. Second
process is difference between current image-s edge map and reference
background image-s edge map, it possible to estimate illumination at
any block. This information is possible to exactly detect object,
artificial illumination and it was generating reference background
more clearly. Block is classified by block-state analysis. Block-state
has a 4 state (i.e. transient, stationary, background, artificial
illumination). Fig. 1 is show characteristic of block-state respectively
[1]. Experimental results show that the presented approach works well
in the presence of illumination variance.
Abstract: In order to obtaining the dynamic evolution image of Tungsten array for foam padding, and to research the form of interaction between Tungsten plasma and foam column, a shadow imaging system of four-frame ultraviolet probe laser (266nm)has been designed on 1MA pulse power device. The time resolution of the system is 2.5ns, and static space resolution is superior to 70μm. The radial shadowgraphy image reveals the whole process from the melting and expansion of solid wire to the interaction of the precursor plasma and the foam, from the pinch to rebound inflation. The image shows the continuous interaction of Tungsten plasma and foam in a form of “Raining" within a time of about 50ns, the plasma shell structure has not been found in the whole period of pinch. The quantitative analysis indicates the minimum pinching speed of the foam column is 1.0×106cm/s, and maximum pinching speed is 6.0×106cm/s, and the axial stagnation diameter is approx 1mm.
Abstract: In this paper, a near lossless image coding scheme
based on Orthogonal Polynomials Transform (OPT) has been
presented. The polynomial operators and polynomials basis operators
are obtained from set of orthogonal polynomials functions for the
proposed transform coding. The image is partitioned into a number of
distinct square blocks and the proposed transform coding is applied to
each of these individually. After applying the proposed transform
coding, the transformed coefficients are rearranged into a sub-band
structure. The Embedded Zerotree (EZ) coding algorithm is then
employed to quantize the coefficients. The proposed transform is
implemented for various block sizes and the performance is
compared with existing Discrete Cosine Transform (DCT) transform
coding scheme.
Abstract: DNA microarray technology is widely used by
geneticists to diagnose or treat diseases through gene expression.
This technology is based on the hybridization of a tissue-s DNA
sequence into a substrate and the further analysis of the image
formed by the thousands of genes in the DNA as green, red or yellow
spots. The process of DNA microarray image analysis involves
finding the location of the spots and the quantification of the
expression level of these. In this paper, a tool to perform DNA
microarray image analysis is presented, including a spot addressing
method based on the image projections, the spot segmentation
through contour based segmentation and the extraction of relevant
information due to gene expression.
Abstract: Polarization-interferometric nonlinear confocal
microscopy is proposed for measuring a nano-sized particle with
optical anisotropy. The anisotropy in the particle was
spectroscopically imaged through a three-dimensional distribution of
third-order nonlinear dielectric polarization photoinduced.
Abstract: We describe a new filtering approach in the wavelet domain for image denoising and compression, based on the projections of details subbands coefficients (resultants of the splitting procedure, typical in wavelet domain) onto the approximation subband coefficients (much less noisy). The new algorithm is called Projection Onto Approximation Coefficients (POAC). As a result of this approach, only the approximation subband coefficients and three scalars are stored and/or transmitted to the channel. Besides, with the elimination of the details subbands coefficients, we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.
Abstract: In this paper, we propose a new robust and secure
system that is based on the combination between two different
transforms Discrete wavelet Transform (DWT) and Contourlet
Transform (CT). The combined transforms will compensate the
drawback of using each transform separately. The proposed
algorithm has been designed, implemented and tested successfully.
The experimental results showed that selecting the best sub-band for
embedding from both transforms will improve the imperceptibility
and robustness of the new combined algorithm. The evaluated
imperceptibility of the combined DWT-CT algorithm which gave a
PSNR value 88.11 and the combination DWT-CT algorithm
improves robustness since it produced better robust against Gaussian
noise attack. In addition to that, the implemented system shored a
successful extraction method to extract watermark efficiently.
Abstract: Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
Abstract: The current research paper is an implementation of
Eigen Faces and Karhunen-Loeve Algorithm for face recognition.
The designed program works in a manner where a unique
identification number is given to each face under trial. These faces
are kept in a database from where any particular face can be matched
and found out of the available test faces. The Karhunen –Loeve
Algorithm has been implemented to find out the appropriate right
face (with same features) with respect to given input image as test
data image having unique identification number. The procedure
involves usage of Eigen faces for the recognition of faces.
Abstract: The counting process of cell colonies is always a long
and laborious process that is dependent on the judgment and ability
of the operator. The judgment of the operator in counting can vary in
relation to fatigue. Moreover, since this activity is time consuming it
can limit the usable number of dishes for each experiment. For these
purposes, it is necessary that an automatic system of cell colony
counting is used. This article introduces a new automatic system of
counting based on the elaboration of the digital images of cellular
colonies grown on petri dishes. This system is mainly based on the
algorithms of region-growing for the recognition of the regions of
interest (ROI) in the image and a Sanger neural net for the
characterization of such regions. The better final classification is
supplied from a Feed-Forward Neural Net (FF-NN) and confronted
with the K-Nearest Neighbour (K-NN) and a Linear Discriminative
Function (LDF). The preliminary results are shown.
Abstract: Copper based composites reinforced with WC and Ti
particles were prepared using planetary ball-mill. The experiment
was designed by using Taguchi technique and milling was carried out
in an air for several hours. The powder was characterized before and
after milling using the SEM, TEM and X-ray for microstructure and
for possible new phases. Microstructures show that milled particles
size and reduction in particle size depend on many parameters. The
distance d between planes of atoms estimated from X-ray powder
diffraction data and TEM image. X-ray diffraction patterns of the
milled powder did not show clearly any new peak or energy shift, but
the TEM images show a significant change in crystalline structure of
corporate on titanium in the composites.
Abstract: In this paper we present an off line system for the
recognition of the handwritten numeric chains. Our work is divided
in two big parts. The first part is the realization of a recognition
system of the isolated handwritten digits. In this case the study is
based mainly on the evaluation of neural network performances,
trained with the gradient back propagation algorithm. The used
parameters to form the input vector of the neural network are
extracted on the binary images of the digits by several methods: the
distribution sequence, the Barr features and the centred moments of
the different projections and profiles. The second part is the
extension of our system for the reading of the handwritten numeric
chains constituted of a variable number of digits. The vertical
projection is used to segment the numeric chain at isolated digits and
every digit (or segment) will be presented separately to the entry of
the system achieved in the first part (recognition system of the
isolated handwritten digits). The result of the recognition of the
numeric chain will be displayed at the exit of the global system.