Abstract: Authentication of multimedia contents has gained much attention in recent times. In this paper, we propose a secure semi-fragile watermarking, with a choice of two watermarks to be embedded. This technique operates in integer wavelet domain and makes use of semi fragile watermarks for achieving better robustness. A self-recovering algorithm is employed, that hides the image digest into some Wavelet subbands to detect possible malevolent object manipulation undergone by the image (object replacing and/or deletion). The Semi-fragility makes the scheme tolerant for JPEG lossy compression as low as quality of 70%, and locate the tempered area accurately. In addition, the system ensures more security because the embedded watermarks are protected with private keys. The computational complexity is reduced using parameterized integer wavelet transform. Experimental results show that the proposed scheme guarantees the safety of watermark, image recovery and location of the tempered area accurately.
Abstract: In order to protect original data, watermarking is first consideration direction for digital information copyright. In addition, to achieve high quality image, the algorithm maybe can not run on embedded system because the computation is very complexity. However, almost nowadays algorithms need to build on consumer production because integrator circuit has a huge progress and cheap price. In this paper, we propose a novel algorithm which efficient inserts watermarking on digital image and very easy to implement on digital signal processor. In further, we select a general and cheap digital signal processor which is made by analog device company to fit consumer application. The experimental results show that the image quality by watermarking insertion can achieve 46 dB can be accepted in human vision and can real-time execute on digital signal processor.
Abstract: Face Recognition is a field of multidimensional
applications. A lot of work has been done, extensively on the most of
details related to face recognition. This idea of face recognition using
PCA is one of them. In this paper the PCA features for Feature
extraction are used and matching is done for the face under
consideration with the test image using Eigen face coefficients. The
crux of the work lies in optimizing Euclidean distance and paving the
way to test the same algorithm using Matlab which is an efficient tool
having powerful user interface along with simplicity in representing
complex images.
Abstract: n-CdO/p-Si heterojunction diode was fabricated using
sol-gel spin coating technique which is a low cost and easily scalable
method for preparing of semiconductor films. The structural and
morphological properties of CdO film were investigated. The X-ray
diffraction (XRD) spectra indicated that the film was of
polycrystalline nature. The scanning electron microscopy (SEM)
images indicate that the surface morphology CdO film consists of the
clusters formed with the coming together of the nanoparticles. The
electrical characterization of Au/n-CdO/p–Si/Al heterojunction diode
was investigated by current-voltage. The ideality factor of the diode
was found to be 3.02 for room temperature. The reverse current of
the diode strongly increased with illumination intensity of 100
mWcm-2 and the diode gave a maximum open circuit voltage Voc of
0.04 V and short-circuits current Isc of 9.92×10-9 A.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: The purpose of the current study is to gain insight into the relative role of professional self-image (PSI) for service providers among leader-member exchange (LMX), career success. Lack of studies demonstrated that PSI of service providers affect on their CS. So, it is necessary to, according to service providers- perspective, explore the relationship among LMX and CS in hospitality industry. The result of the current study can suggest strategic directions for hospitality practitioners in terms of constructing LMX relationship, so as to make service providers realize and build their PSI, and to promote their CS. Implications of these findings for hospitality implementations as well as future research directions are subsequently discussed.
Abstract: In this paper, we propose a high capacity image hiding
technology based on pixel prediction and the difference of modified histogram. This approach is used the pixel prediction and the
difference of modified histogram to calculate the best embedding point.
This approach can improve the predictive accuracy and increase the pixel difference to advance the hiding capacity. We also use the
histogram modification to prevent the overflow and underflow. Experimental results demonstrate that our proposed method within the
same average hiding capacity can still keep high quality of image and low distortion
Abstract: In this paper, a new reversible watermarking method is presented that reduces the size of a stereoscopic image sequence while keeping its content visible. The proposed technique embeds the residuals of the right frames to the corresponding frames of the left sequence, halving the total capacity. The residual frames may result in after a disparity compensated procedure between the two video streams or by a joint motion and disparity compensation. The residuals are usually lossy compressed before embedding because of the limited embedding capacity of the left frames. The watermarked frames are visible at a high quality and at any instant the stereoscopic video may be recovered by an inverse process. In fact, the left frames may be exactly recovered whereas the right ones are slightly distorted as the residuals are not embedded intact. The employed embedding method reorders the left frame into an array of consecutive pixel pairs and embeds a number of bits according to their intensity difference. In this way, it hides a number of bits in intensity smooth areas and most of the data in textured areas where resulting distortions are less visible. The experimental evaluation demonstrates that the proposed scheme is quite effective.
Abstract: One of the most important problems to solve is eye
location for a driver fatigue monitoring system. This paper presents an
efficient method to achieve fast and accurate eye location in grey level
images obtained in the real-word driving conditions. The structure of
eye region is used as a robust cue to find possible eye pairs. Candidates
of eye pair at different scales are selected by finding regions which
roughly match with the binary eye pair template. To obtain real one,
all the eye pair candidates are then verified by using support vector
machines. Finally, eyes are precisely located by using binary vertical
projection and eye classifier in eye pair images. The proposed method
is robust to deal with illumination changes, moderate rotations, glasses
wearing and different eye states. Experimental results demonstrate its
effectiveness.
Abstract: We describe a work with an evolutionary computing
algorithm for non photo–realistic rendering of a target image. The
renderings are produced by genetic programming. We have used two
different types of strokes: “empty triangle" and “filled triangle" in
color level. We compare both empty and filled triangular strokes to
find which one generates more aesthetic pleasing images. We found
the filled triangular strokes have better fitness and generate more
aesthetic images than empty triangular strokes.
Abstract: Recently, majors of doctors are divided into terribly lots of detailed areas. However, it is actually not a rare case that a doctor has a patient who is not in his/her major. He/She must judge an assessment and make a medical treatment plan for this patient. According to our investigation, conventional approaches such as image diagnosis cooperation are insufficient. This paper proposes an 'Assessment / Medical Treatment Plan Consulting System'. We have implemented a pilot system based on our proposition. Its effectiveness is clarified by an evaluation.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images and set up compression-transmit schemes to distribute result to the remote doctor. To achieve this goal, we use basically a level-sets approach to delineating brain tumors in threedimensional. Then introduce a new compression and transmission 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 wireless network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: In this investigation, anatase TiO2 thin films were
grown by radio frequency magnetron sputtering on glass substrates at
a high sputtering pressure and room temperature. The anatase films
were then annealed at 300-600 °C in air for a period of 1 hour. To
examine the structure and morphology of the films, X-ray diffraction
(XRD) and atomic force microscopy (AFM) methods were used
respectively. From X-ray diffraction patterns of the TiO2 films, it was
found that the as-deposited film showed some differences compared
with the annealed films and the intensities of the peaks of the
crystalline phase increased with the increase of annealing
temperature. From AFM images, the distinct variations in the
morphology of the thin films were also observed. The optical
constants were characterized using the transmission spectra of the
films obtained by UV-VIS-IR spectrophotometer. Besides, optical
thickness of the film deposited at room temperature was calculated
and cross-checked by taking a cross-sectional image through SEM.
The optical band gaps were evaluated through Tauc model. It was
observed that TiO2 films produced at room temperatures exhibited
high visible transmittance and transmittance decreased slightly with
the increase of annealing temperatures. The films were found to be
crystalline having anatase phase. The refractive index of the films
was found from 2.31-2.35 in the visible range. The extinction
coefficient was nearly zero in the visible range and was found to
increase with annealing temperature. The allowed indirect optical
band gap of the films was estimated to be in the range from 3.39 to
3.42 eV which showed a small variation. The allowed direct band
gap was found to increase from 3.67 to 3.72 eV. The porosity was
also found to decrease at a higher annealing temperature making the
film compact and dense.
Abstract: In this paper, we present a robust and secure
algorithm for watermarking, the watermark is first transformed into
the frequency domain using the discrete wavelet transform (DWT).
Then the entire DWT coefficient except the LL (Band) discarded,
these coefficients are permuted and encrypted by specific mixing.
The encrypted coefficients are inserted into the most significant
spectral components of the stego-image using a chaotic system. This
technique makes our watermark non-vulnerable to the attack (like
compression, and geometric distortion) of an active intruder, or due
to noise in the transmission link.
Abstract: The structure of retinal vessels is a prominent feature,
that reveals information on the state of disease that are reflected in
the form of measurable abnormalities in thickness and colour.
Vascular structures of retina, for implementation of clinical diabetic
retinopathy decision making system is presented in this paper.
Retinal Vascular structure is with thin blood vessel, whose accuracy
is highly dependent upon the vessel segmentation. In this paper the
blood vessel thickness is automatically detected using preprocessing
techniques and vessel segmentation algorithm. First the capture
image is binarized to get the blood vessel structure clearly, then it is
skeletonised to get the overall structure of all the terminal and
branching nodes of the blood vessels. By identifying the terminal
node and the branching points automatically, the main and branching
blood vessel thickness is estimated. Results are presented and
compared with those provided by clinical classification on 50 vessels
collected from Bejan Singh Eye hospital..
Abstract: In this paper an algorithm is used to detect the color defects of ceramic tiles. First the image of a normal tile is clustered using GCMA; Genetic C-means Clustering Algorithm; those results in best cluster centers. C-means is a common clustering algorithm which optimizes an objective function, based on a measure between data points and the cluster centers in the data space. Here the objective function describes the mean square error. After finding the best centers, each pixel of the image is assigned to the cluster with closest cluster center. Then, the maximum errors of clusters are computed. For each cluster, max error is the maximum distance between its center and all the pixels which belong to it. After computing errors all the pixels of defected tile image are clustered based on the centers obtained from normal tile image in previous stage. Pixels which their distance from their cluster center is more than the maximum error of that cluster are considered as defected pixels.
Abstract: An important step in studying the statistics of
fingerprint minutia features is to reliably extract minutia features from
the fingerprint images. A new reliable method of computation for
minutiae feature extraction from fingerprint images is presented. A
fingerprint image is treated as a textured image. An orientation flow
field of the ridges is computed for the fingerprint image. To
accurately locate ridges, a new ridge orientation based computation
method is proposed. After ridge segmentation a new method of
computation is proposed for smoothing the ridges. The ridge skeleton
image is obtained and then smoothed using morphological operators
to detect the features. A post processing stage eliminates a large
number of false features from the detected set of minutiae features.
The detected features are observed to be reliable and accurate.
Abstract: Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.
Abstract: Image convolution similar to the receptive fields
found in mammalian visual pathways has long been used in
conventional image processing in the form of Gabor masks.
However, no VLSI implementation of parallel, multi-layered pulsed
processing has been brought forward which would emulate this
property. We present a technical realization of such a pulsed image
processing scheme. The discussed IC also serves as a general testbed
for VLSI-based pulsed information processing, which is of interest
especially with regard to the robustness of representing an analog
signal in the phase or duration of a pulsed, quasi-digital signal, as
well as the possibility of direct digital manipulation of such an
analog signal. The network connectivity and processing properties
are reconfigurable so as to allow adaptation to various processing
tasks.
Abstract: We present a new method for the fully automatic 3D
reconstruction of the coronary artery centerlines, using two X-ray
angiogram projection images from a single rotating monoplane
acquisition system. During the first stage, the input images are
smoothed using curve evolution techniques. Next, a simple yet
efficient multiscale method, based on the information of the Hessian
matrix, for the enhancement of the vascular structure is introduced.
Hysteresis thresholding using different image quantiles, is used to
threshold the arteries. This stage is followed by a thinning procedure
to extract the centerlines. The resulting skeleton image is then pruned
using morphological and pattern recognition techniques to remove
non-vessel like structures. Finally, edge-based stereo correspondence
is solved using a parallel evolutionary optimization method based on
f symbiosis. The detected 2D centerlines combined with disparity
map information allow the reconstruction of the 3D vessel
centerlines. The proposed method has been evaluated on patient data
sets for evaluation purposes.