Abstract: This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.
Abstract: Motion capture devices have been utilized in
producing several contents, such as movies and video games. However,
since motion capture devices are expensive and inconvenient to use,
motions segmented from captured data was recycled and synthesized
to utilize it in another contents, but the motions were generally
segmented by contents producers in manual. Therefore, automatic
motion segmentation is recently getting a lot of attentions. Previous
approaches are divided into on-line and off-line, where on-line
approaches segment motions based on similarities between
neighboring frames and off-line approaches segment motions by
capturing the global characteristics in feature space. In this paper, we
propose a graph-based high-level motion segmentation method. Since
high-level motions consist of several repeated frames within temporal
distances, we consider all similarities among all frames within the
temporal distance. This is achieved by constructing a graph, where
each vertex represents a frame and the edges between the frames are
weighted by their similarity. Then, normalized cuts algorithm is used
to partition the constructed graph into several sub-graphs by globally
finding minimum cuts. In the experiments, the results using the
proposed method showed better performance than PCA-based method
in on-line and GMM-based method in off-line, as the proposed method
globally segment motions from the graph constructed based
similarities between neighboring frames as well as similarities among
all frames within temporal distances.
Abstract: We present a hardware oriented method for real-time
measurements of object-s position in video. The targeted application
area is light spots used as references for robotic navigation. Different
algorithms for dynamic thresholding are explored in combination
with component labeling and Center Of Gravity (COG) for highest
possible precision versus Signal-to-Noise Ratio (SNR). This method
was developed with a low hardware cost in focus having only one
convolution operation required for preprocessing of data.
Abstract: FAQ system can make user find answer to the problem that puzzles them. But now the research on Chinese FAQ system is still on the theoretical stage. This paper presents an approach to semantic inference for FAQ mining. To enhance the efficiency, a small pool of the candidate question-answering pairs retrieved from the system for the follow-up work according to the concept of the agriculture domain extracted from user input .Input queries or questions are converted into four parts, the question word segment (QWS), the verb segment (VS), the concept of agricultural areas segment (CS), the auxiliary segment (AS). A semantic matching method is presented to estimate the similarity between the semantic segments of the query and the questions in the pool of the candidate. A thesaurus constructed from the HowNet, a Chinese knowledge base, is adopted for word similarity measure in the matcher. The questions are classified into eleven intension categories using predefined question stemming keywords. For FAQ mining, given a query, the question part and answer part in an FAQ question-answer pair is matched with the input query, respectively. Finally, the probabilities estimated from these two parts are integrated and used to choose the most likely answer for the input query. These approaches are experimented on an agriculture FAQ system. Experimental results indicate that the proposed approach outperformed the FAQ-Finder system in agriculture FAQ retrieval.
Abstract: In this study, we present a new and fast algorithm for lung segmentation using CTA images. This process is quite important especially at lung vessel segmentation, detection of pulmonary emboly, finding nodules or segmentation of airways. Applied method has been carried out at four steps. At first step, images have been applied optimal threshold. At the second one, the subsegment vessels, which have a place in lung region and which are in small dimension, have been removed. At the third one, identifying and segmentation of lungs and airway edges have been carried out. Lastly, by throwing away the airway, lung segmentation has been presented.
Abstract: In this paper, a new automated methodology to detect the optic disc (OD) automatically in retinal images from patients with risk of being affected by Diabetic Retinopathy (DR) and Macular Edema (ME) is presented. The detection procedure comprises two independent methodologies. On one hand, a location methodology obtains a pixel that belongs to the OD using image contrast analysis and structure filtering techniques and, on the other hand, a boundary segmentation methodology estimates a circular approximation of the OD boundary by applying mathematical morphology, edge detection techniques and the Circular Hough Transform. The methodologies were tested on a set of 1200 images composed of 229 retinographies from patients affected by DR with risk of ME, 431 with DR and no risk of ME and 540 images of healthy retinas. The location methodology obtained 98.83% success rate, whereas the OD boundary segmentation methodology obtained good circular OD boundary approximation in 94.58% of cases. The average computational time measured over the total set was 1.67 seconds for OD location and 5.78 seconds for OD boundary segmentation.
Abstract: PROFIBUS (PROcess FIeld BUS) which is defined with international standarts (IEC61158, EN50170) is the most popular fieldbus, and provides a communication between industrial applications which are located in different control environment and location in manufacturing, process and building automation. Its communication speed is from 9.6 Kbps to 12 Mbps over distances from 100 to 1200 meters, and so it is to be often necessary to interconnect them in order to break these limits. Unfortunately this interconnection raises several issues and the solutions found so far are not very satisfactory. In this paper, we propose a new solution to interconnect PROFIBUS segments, which uses a wireless MAN based on the IEEE 802.16 standard as a backbone system. Also, the solution which is described a model for internetworking unit integrates the traffic generated by PROFIBUS segments into IEEE 802.16 wireless MAN using encapsulation technique.
Abstract: Chinese Idioms are a type of traditional Chinese idiomatic
expressions with specific meanings and stereotypes structure
which are widely used in classical Chinese and are still common in
vernacular written and spoken Chinese today. Currently, Chinese
Idioms are retrieved in glossary with key character or key word in
morphology or pronunciation index that can not meet the need of
searching semantically. OCIRS is proposed to search the desired
idiom in the case of users only knowing its meaning without any key
character or key word. The user-s request in a sentence or phrase will
be grammatically analyzed in advance by word segmentation, key
word extraction and semantic similarity computation, thus can be
mapped to the idiom domain ontology which is constructed to provide
ample semantic relations and to facilitate description logics-based
reasoning for idiom retrieval. The experimental evaluation shows that
OCIRS realizes the function of searching idioms via semantics, obtaining
preliminary achievement as requested by the users.
Abstract: The image segmentation method described in this
paper has been developed as a pre-processing stage to be used in
methodologies and tools for video/image indexing and retrieval by
content. This method solves the problem of whole objects extraction
from background and it produces images of single complete objects
from videos or photos. The extracted images are used for calculating
the object visual features necessary for both indexing and retrieval
processes.
The segmentation algorithm is based on the cooperation among an
optical flow evaluation method, edge detection and region growing
procedures. The optical flow estimator belongs to the class of
differential methods. It permits to detect motions ranging from a
fraction of a pixel to a few pixels per frame, achieving good results in
presence of noise without the need of a filtering pre-processing stage
and includes a specialised model for moving object detection.
The first task of the presented method exploits the cues from
motion analysis for moving areas detection. Objects and background
are then refined using respectively edge detection and seeded region
growing procedures. All the tasks are iteratively performed until
objects and background are completely resolved.
The method has been applied to a variety of indoor and outdoor
scenes where objects of different type and shape are represented on
variously textured background.
Abstract: Automated production lines with so called 'hard structures' are widely used in manufacturing. Designers segmented these lines into sections by placing a buffer between the series of machine tools to increase productivity. In real production condition the capacity of a buffer system is limited and real production line can compensate only some part of the productivity losses of an automated line. The productivity of such production lines cannot be readily determined. This paper presents mathematical approach to solving the structure of section-based automated production lines by criterion of maximum productivity.
Abstract: In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.
Abstract: Stegnography is a new way of secret
communication the most widely used mechanism on account
of its simplicity is the use of the least significant bit. We have
used the least significant bit (2 LSB and 4 LSB) substitution
method. Depending upon the characteristics of the individual
portions of cover image we decide whether to use 2 LSB or 4
LSB thus it is an adaptive stegnography technique. We used
one of the three channels to behave as indicator to indicate the
presence of hidden data in other two channels. The module
showed impressive results in terms of capacity to hide the
data. In proposed method, instead of using RGB color space
directly, YCbCr color space is used to make use of human
visual system characteristic.
Abstract: The last two decades witnessed some advances in the development of an Arabic character recognition (CR) system. Arabic CR faces technical problems not encountered in any other language that make Arabic CR systems achieve relatively low accuracy and retards establishing them as market products. We propose the basic stages towards a system that attacks the problem of recognizing online Arabic cursive handwriting. Rule-based methods are used to perform simultaneous segmentation and recognition of word portions in an unconstrained cursively handwritten document using dynamic programming. The output of these stages is in the form of a ranked list of the possible decisions. A new technique for text line separation is also used.
Abstract: In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.
Abstract: Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.
Abstract: The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.
Abstract: In this paper we propose a novel method for human
face segmentation using the elliptical structure of the human head. It
makes use of the information present in the edge map of the image.
In this approach we use the fact that the eigenvalues of covariance
matrix represent the elliptical structure. The large and small
eigenvalues of covariance matrix are associated with major and
minor axial lengths of an ellipse. The other elliptical parameters are
used to identify the centre and orientation of the face. Since an
Elliptical Hough Transform requires 5D Hough Space, the Circular
Hough Transform (CHT) is used to evaluate the elliptical parameters.
Sparse matrix technique is used to perform CHT, as it squeeze zero
elements, and have only a small number of non-zero elements,
thereby having an advantage of less storage space and computational
time. Neighborhood suppression scheme is used to identify the valid
Hough peaks. The accurate position of the circumference pixels for
occluded and distorted ellipses is identified using Bresenham-s
Raster Scan Algorithm which uses the geometrical symmetry
properties. This method does not require the evaluation of tangents
for curvature contours, which are very sensitive to noise. The method
has been evaluated on several images with different face orientations.
Abstract: Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs from magnetic resonance images. Materials and methods: Thirty obese women were scanned on a Siemens Impact Expert 1T resonance machine. 1500 images were finally used in the tests. The developed segmentation method is a recursive and multilevel process that makes use of several concepts such as shaped histograms, adaptative thresholding and connectivity. The segmentation process was implemented in Matlab and operates without the need of any user interaction. The whole set of images were segmented with the developed method. An expert radiologist segmented the same set of images following a manual procedure with the aid of the SliceOmatic software (Tomovision). These constituted our 'goal standard'. Results: The number of coincidental pixels of the automatic and manual segmentation procedures was measured. The average results were above 90 % of success in most of the images. Conclusions: The proposed approach allows effective automatic segmentation of MRIs from thighs, comparable to expert manual performance.
Abstract: The effect of autofrettage process in strain hardened
thick-walled pressure vessels has been investigated theoretically by
finite element modeling. Equivalent von Mises stress is used as yield
criterion to evaluate the optimum autofrettage pressure and the
optimum radius of elastic-plastic junction. It has been observed that
the optimum autofrettage pressure increases along with the working
pressure. For two different working pressures, the effect of the ratio
of outer to inner radius (b/a=k) value on the optimum autofrettage
pressure is also noticed. The Optimum autofrettage pressure solely
depends on K value rather than on the inner or outer radius.
Furthermore, percentage reduction of von Mises stresses is compared
for different working pressures and different k values. Maximum von
Mises stress developed at different autofrettage pressure is equated
for elastic perfectly plastic and elastic-plastic material with different
slope of strain hardening segment. Cylinder material having higher
slope of strain hardening segment provides better benedictions in the
autofrettage process.
Abstract: The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.