Estimation of Moments For Low And High Snr Atmospheric Radar Data

Vol.1 No.3

Year: 2012

Issue: May-Jul

Title: Estimation of Moments For Low And High Snr Atmospheric Radar Data   

Author Name: PADMAJA NIMMAGADDA, G. Madhavi Latha , S.Varadarajan   

Synopsis: 

Atmospheric Signal processing  has been one field of signal  processing where    there is a  lot of scope for development of new and efficient tools for Cleaning of the spectrum, detection and estimation of the desired parameters. Atmospheric signal processing deals with the processing of the signals received from the atmosphere. The signals,  which are processed in the present work, have been  obtained from the mesosphere - stratosphere-  troposphere (MST) Radar. The MST radar   facilities are situated at National Atmospheric research Laboratory, Gadanki, and  Tirupati, India. The signal processing done in the present work concentrates  mainly on  the data collected from NARL located at Gadanki. This work deals with signal processing     techniques used for the analysis of MST Radar  signal and to extract better information about moments for wind   profilling. The proposed algorithm estimates radar moments and signal to noise ratio. The performance of this method is tested practically with atmospheric wind profiler data ADP (Atmospheric Data Processor). Signal processing of recoded experimental data  is performed using Matlab. Moments were estimated using five peak method and results are plotted.         

Evaluation Metric Standardization for Edge detection and Enhancement algorithms

Vol.1 No.3

Year: 2012

Issue: May-Jul

Title: Evaluation Metric Standardization for Edge detection and Enhancement algorithms   

Author Name: Abhishek Gudipalli, Dr.T.Ramashri   

Synopsis:                 

Pattern recognition, Image enhancement, Feature extraction are the key research areas in image processing. It can be applied to many applications such as satellite, medical, military, infrared imaging and LIDAR. There are many existing algo in im pr, several image enhancement techniques have been developed, such as histogram equalization, contrast stretching, bit plane slicing, averaging, etc. but the ambiguity is because of missing evaluation metrics, which leads to uncertainity in deciding the algorithm that can perform better. There are some uncertainties regarding these above techniques such as edge detection, oversmoothing, blurring and deformation of edges. In this paper, we considered edge detection as one of the uncertainty and the evaluation metrics such as SSIM (Structural Similarity Index) and VIF(Visual Information Fidelity) has been applied to the images to measure the image quality. The SSIM and VIF have been applied to the different types of images such as Grayscale, Color, Infrared, LIDAR, Microscopic and Biomedical Images. In the present work evaluation metrics are applied to the original image and egde detected image, thus from experimental results it is observed that the proposed algorithm works well for measuring the quality of spatial resolution enhanced   hyper spectral images

Offline Ancient Tamil Character Recognition System Based On Structural Features

Vol.1 No.3

Year: 2012

Issue: May-Jul

Title: Offline Ancient Tamil Character Recognition System Based On Structural Features   

Author Name: S. Rajakumar, V. Subbiah Bharathi   

Synopsis:   

In this paper we propose an approach for offline recognition of ancient Tamil characters using their structural features. Structural features are the features that are physically a part of the structure of the character, such as straight lines, arcs, circles, intersections etc. The features used for recognition are the positions of vertical lines, horizontal lines and branching in a character. Some other features, namely moments, zoning and number of transitions have also been explored to verify their utility in Tamil character recognition. For classification of the characters simple Euclidean distance was used. Ancient Tamil Character recognition is a classic problem in the field of image processing and neural networks. Lot of research has been done on recognition of handwritten Tamil characters but relatively less work has been done in the field of recognition of Ancient Tamil characters in Indian languages. In this paper we explore some structural features that can be used in offline Ancient Tamil character recognition. Structural features are insufficient to classify all the characters. Some other features along with the use of artificial neural networks can improve the performance of the system. The proposed algorithm obtained results in terms of accuracy (reaches 97.9% for some letters at average 80%) as well as in terms of time consuming.

Transient Scattering by Dielectric bodies-A Comparison of TLM and TDIE Methods

Vol.1 No.3

Year: 2012

Issue: May-Jul

Title : Transient Scattering by Dielectric bodies-A Comparison of TLM and TDIE Methods   

Author Name: R. Srinivasa Rao, P.V. Subbaiah , B. Prabhakara Rao   

Synopsis:   

The radar signature calculations play an essential role in the design and functioning of today’s radars in detecting the surface and air targets.  Radar interrogation is essentially a transient electromagnetic scattering process and direct transient analysis provides an opportunity to observe and to interpret scattering behavior.  We present in this paper a comparison of two popular time domain numerical techniques widely used for direct transient analysis, namely, the transmission line matrix (TLM) method and the time-domain integral equation (TDIE) method. Both the methods belong to the category of time domain techniques; however, their modeling philosophy is quite different. Whereas the TLM method is based on the implementation of the Huygens principle by modeling the space with a system of interconnected transmission-lines, the TDIE is based on well known method of moments. The comparison is made via standard canonical shaped dielectric bodies, namely, a cube, and a sphere, mainly to address the factors affecting accuracy, efficiency, and the required computer resources.

An Overview of Class Imbalance Problem in Supervised Learning

Vol.1 No.3

Year: 2012

Issue: May-Jul

Title: An Overview of Class Imbalance Problem in Supervised Learning   

Author Name: Satuluri Naganjaneyulu, Mrithyumjaya Rao Kuppa   

Synopsis: 

In Data mining and Knowledge Discovery hidden and valuable knowledge from the data sources is discovered. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability.  Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class(es).  This paper presents an updated literature survey of current class imbalance learning methods for inducing models which handle imbalanced datasets efficiently.

Evolutionary Approach of Adiabatic Logic Design on Low Power Solution –A Robust Survey

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Evolutionary Approach of Adiabatic Logic Design on Low Power Solution –A Robust Survey

Author Name: A. Kishore Kumar, D. Somasundareswari , V.Duraisamy , T. Shunbaga Pradeepa   

Synopsis:                           

 Adiabatic Logic styles in low power VLSI design have been examined for many years to achieve predictable low power design success.  In this paper, we present a comprehensive literature review pertaining to the state-of-the-art issues in adiabatic logic designs and also focus on primary developments in this field that have taken place in the low power design. Various research papers and application notes have been referred to, for clear understanding of adiabatic logic designs on low power solutions. Major focus of this paper is to identify the gaps of the adiabatic logic designs and to narrow down the problems and requirements for its practical usage in semiconductor industries. Enough designs and methods have been proposed over last few decades, but the implementation of this logic, triggers the designer in various open points, which restricts further stems. This paper highlights the major open points and gives the solution for further design requirement to implement the adiabatic logic in semiconductor industries.

 

 

  

 

Comparative Study of Different Medical Images with Noise Based On Morphology

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Comparative Study of Different Medical Images with Noise Based On Morphology   

Author Name: V. Kalpana, T. Surendra Nath , Vijaya Kishore                                

Synopsis:   

Medical images are diagnosed and demonstrated with their regional structures. Edge detection is a fundamental element in the field of image processing and computer vision for the extraction of features. Edge detection identifies and captures sharp intensity changes in an image. Medical image edge detection focus on object recognition of human organs. To detect the severity of disease several medical approaches like CT, MRI, PET, US and DICOM can be used. In this paper performance of CT and DICOM images using morphology and edge detection algorithms are evaluated in noisy environment. A comparision of different edge detecting algorithms by using several noises is performed and evaluated based on correlation coefficient and PSNR. The outcomes evaluate the resistivity of operators in presence of noise.

 

  

 

Analysis of Planar Tapered Dielectric Optical Waveguides using Matrix Approach without Considering the Reflection of the Fields at the Taper Boundary

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Analysis of Planar Tapered Dielectric Optical Waveguides using Matrix Approach without Considering the Reflection of the Fields at the Taper Boundary   

Author Name: S. K. Raghuwanshi, S. Kumar   

Synopsis:   

Optical waveguides are the building blocks of photonics circuits. They are used as, couplers, switches, splitters, multiplexer and de-multiplexer for optical signals. During the last two decades extensive study on analytical/numerical method in the field of optical waveguide has been done by different researchers. In this paper the matrix method has been applied to analyze taper waveguide (or bend waveguide) while considering the normal incidence of light and assumed to be no reflection from the first medium, where the light is being launched. The waveguide is assumed to be taper (bend). This type of waveguide structure is used in WDM optical communication system as a power splitter device.

 

  

 

Performance Analysis of CDMA System Using Power Control Algorithm With AWGN Channel

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Performance Analysis of CDMA System Using Power Control Algorithm With AWGN Channel   

Author Name: G. Brindha   

Synopsis:                        

Continuation of an active call is one of the most important quality measures in cellular communication systems. Handoff process in the cellular system  enables  to provide such  facility by transferring an active call from one cell to another cell.Signals transmitted over a multipath propagation channel can exhibits inter path interference and fading. To overcome the multipath effect, Rake receiver is used in CDMA technology. An important characteristic of a multipath channel is the time delay spread it causes to the received signal. This delay spread equals the time delay between the arrival of the first received signal component (LOS or multipath) and the last received signal component associated with a single transmitted pulse. Another characteristic of the multipath channel is its time-varying nature.Rake receiver is realized between the main path component and the local recovery carrier. In this paper the downlink performance parameters are estimated for a CDMA mobile system at the vertex of multiple adjacent cells. At the base station the received signal is coherently dispread and demodulated using a rake receiver. The effects of power control, error correction and rake receiver were also investigated and simulated based on the assumption that the received signals undergo Rayleigh fading.

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Curvelets with New Quantizer for Image Compression

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Curvelets with New Quantizer for Image Compression                   

Author Name: G. Jagadeeswar Reddy, T. Jaya Chandra Prasad , Giri Prasad M.N, M. Madhavi Latha , T. Satya Savithri   

Synopsis:   

This paper emphasizes on designing of a novice quantizer that is more suitable for compressing images through new transform known as curvelet transform. The new transform is believed to capture image information more efficiently than the wavelet transform by providing basis elements in addition to possessing the qualities of wavelet. It was designed to represent edges and other singularities along curves much more efficiently than traditional transforms, i.e. using many fewer coefficients for a given accuracy of reconstruction. This compression algorithm is tested on various images like plain, textured and building images. The results are compared with the existing techniques like curvelet with existing quatizer, wavelet with existing quantizer and wavelet with proposed quantzer. The proposed algorithm “curvelets with proposed quantizer” outperforms the existing techniques. The performance is evaluated through visual clarity, Peak Signal to Noise Ratio (PSNR) and compression metrics such as Compression ratio and Bit-rate.

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Roi Segmentation On Dicom Image In Presence Of Noise Based On Morphology

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Roi Segmentation On Dicom Image In Presence Of Noise Based On Morphology   

Author Name: T. Surendra Nath, V. Kalpana , Vijaya Kishore   

Synopsis:   

Various medical imaging available are MRI, CT, US and DICOM. Automated Computer Aided Diagnosing (CAD) system detects lung cancer with improved diagnostic radiology. Several approaches to lung CAD combine geometric and intensity models to enhance local anatomical structure. Two difficulties those are primarily associated with the detection of nodules include the detection of nodules that are adjacent to vessels or the chest wall when they have very similar intensity; and the detection of nodules that are non-spherical in shape. In such cases, intensity thresholding or model based methods might fail to identify those nodules. In this paper Region of interest segmentation of DICOM lung image is performed in the noisy environment such as Poisson and speckle using morphology and watershed algorithm. The ROI lung area blood vessels and nodules from the major lung portion are extracted achieved using different edge detection operators such as Sobel, Prewitt and LoG in presence of noise.  The results are helpful to study and analyse the influence of noises on the DICOM images in extracting region of interest.

 

  

 

Analysis of Atmospheric Radar Echoes Using Fft And Matched Filter For Doppler Profile Detection

Vol.1 No.2

Year: 2012

Issue: Feb-Apr

Title: Analysis of Atmospheric Radar Echoes Using Fft And Matched Filter For Doppler Profile Detection   

Author Name: PADMAJA NIMMAGADDA, S.Varadarajan   

Synopsis:   

A new algorithm for Doppler profile detection of Radar echoes using Matched Filter is developed in this paper. The algorithm is applied to the time series radar data obtained from the mesosphere- stratosphere- troposphere (MST) region near Gadanki, Tirupati Matched filter is often referred to as optimum filter. The most unique characteristic of the matched filter is that it produces the maximum achievable instantaneous SNR at its output when a signal plus additive white noise is present at the input.  This presents a new technique adopted when information regarding all the range bins is available and the processing load can be handled. The results are compared with the traditional FFT technique and are presented for the performance evaluation. The merits and limitations of this method of detecting dopplers in comparison to FFT are discussed.

 

Vehicular Ad Hoc Networks in Automotive and Traffic Applications

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Vehicular Ad Hoc Networks in Automotive and Traffic Applications   

Author Name: Gerardine Mary   

Synopsis:   

The goal of this work is to implement vehicle-to-infrastructure and vehicle-to-vehicle communications, creating wireless ad-hoc vehicle networks, or Vehicular Ad Hoc Networks (VANETs). The objective is to specify, design and implement embedded systems and wireless communication protocols in which distance, position and identity information is combined with mobile ad-hoc networking to create the possibility to implement all kinds of localized applications in vehicular environments.

Separation of Heart Sound signal from Lung sound signal using an Adaptive Line Enhancer

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Separation of Heart Sound signal from Lung sound signal using an Adaptive Line Enhancer   

Author Name: S. Vijayalakshmi   

Synopsis:   

Lung sound signal (LSS) measurements are taken to aid in the diagnosis of various diseases. Their interpretation is difficult however due to the presence of interference generated by the heart. In this paper, the adaptive line enhancer (ALE) is employed for reducing heart sound signal (HSS) from lung sound recordings. In this paper thirteen day new born baby girl’s lung sound signal is taken as an input to an adaptive line enhancer, and for updating the weights LMS algorithm has used. This performance is done by using MATLAB 7.0. More over linear predictive FIR filter is used for detecting the interference from the input signal. The architecture is validated in MATLAB, SNR and MSE are calculated. Verilog code is written and ALE has been successfully modeled and has been synthesized using Xilinx 9.1i, cadence and synopsis. The Area, power and timing reports are compared using these three tools. The ASIC design is carried on Synopsys tools.

Comparison of Wavelet Transforms For Denoising And Analysis Of PCG Signal

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Comparison of Wavelet Transforms For Denoising And Analysis Of PCG Signal   

Author Name: Abhishek Misal, Dr.G.R. Sinha, R.P. Gakkhar , M. Kowar   

Synopsis:   

This paper address the PCG signals (Phonocardiogram) and their De-noising techniques. The PCG as a kind of weak biological signal under the back ground of strong noise is easily subject to interference from noise of various sources. De-noising of PCG signal therefore, forms the primary basis for achieving non-invasive diagnosis of coronary heart disease. There are various method are available for De-noising the PCG signal but the method is most effective for the PCG signal is very much important. In this paper de- noise the 4 types of PCG signal and check the different parameters and find that which wavelet gives the maximum result for all four types PCG signals.

Offline Handwritten Devnagari Signature Recognition using Moment Invariant Analysis in Neural Network

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Offline Handwritten Devnagari Signature Recognition using Moment Invariant Analysis in Neural Network   

Author Name: Sandeep Patil, Shailendra Dewangan   

Synopsis:   

Development of a Character recognition system for Devnagari is difficult because (i) there are about 350 basic, modified (“matra”) and compound character shapes in the script and (ii) the characters in words are topologically connected. Here focus is on the recognition of offline handwritten Devnagari signatures that can be used in common applications like bank cheques, commercial forms, government records, bill processing systems, Postcode Recognition, Signature Verification, passport readers, offline document recognition generated by the expanding technological society. Challenges in handwritten signature recognition lie in the variation and distortion of handwritten signature or script since different people may use different style of handwriting, and direction to draw the same shape of any Devnagari character. This overview describes the nature of handwritten language, how it is translated into electronic data, and the basic concepts behind written language recognition algorithms. Handwritten Devnagari signatures are imprecise in nature as their corners are not always sharp, lines are not perfectly straight, and curves are not necessarily smooth, unlikely the printed character. An approach using Artificial Neural Network is considered for recognition of Handwritten Devnagari Signature. The learning process inherent in Neural Networks (NN) can be applied to the process of verifying handwritten signatures that are electronically captured via a stylus. This paper presents a method for verifying handwritten signatures by using NN architecture. Various static (e.g., area covered, number of elements, height, slant, etc.) (Plamondon & Srihari, 2000, p. 63-84) and dynamic (e.g., velocity, pen tip pressure, etc.) signature features are extracted and used to train the NN (Daramola & Ibiyemi, 2010, p. 48-52). Several Network topologies are tested and their accuracy is compared. Although the verification process can be thought to as a monolith component, it is recommended to divide it into loosely coupled phases (like preprocessing, feature extraction, feature matching, feature comparison and classification) allowing us to gain a better control over the precision of different components. This paper focuses on classification, the last phase in the process, covering some of the most important general approaches in the field. Each approach is evaluated for applicability in signature verification, identifying their strength and weaknesses. It is shown, that some of these weak points are common between the different approaches and can partially be eliminated with our proposed solutions. To demonstrate this, several local features are introduced and compared using different classification approaches.

 

Mobile Wireless Channel Dispersion State Recognition An Enabling Cognitive Radio Environmental Awareness Algorithm

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Mobile Wireless Channel Dispersion State Recognition An Enabling Cognitive Radio Environmental Awareness Algorithm   

Author Name: Kenneth Brown, Glenn Prescott   

Synopsis:   

Communication messages to and from mobile wireless users commonly transit combined wired and wireless subnets which are vulnerable to time variant mobile wireless channel conditions.  General cases include: 1) non-dispersive free space loss, 2) non-dispersive fading, 3) time dispersive distortion, 4) frequency dispersive distortion, and 5) dual time and frequency dispersive distortion. Cognitive processing architectures (CPA) can mitigation these problematic conditions with channel state recognition (CSR) algorithms which respond to time-variant distortion without the aid of training sequences or pilot tones.  They can provide efficient distortion state awareness to downstream cognitive processes; which apply near real time mitigation selections among SNR loss, flat-fading, inter-symbol interference (ISI), and/or inter-frequency interference (IFI) methods. This paper covers recent research by the authors to introduce channel state recognition (CSR) algorithms, a CSR testbed, and a reference waveform generator (RWG).  The CSR testbed provides an integrated environment for algorithm verification, and the RWG provides symbol streams with controlled channel states based on calibrated symbol and channel parameters.  Applying reference waveforms to CSR algorithms provides effective algorithm performance verification.  This paper also surveys published wireless channel multistate hidden Markov models (HMM) revealing mature generative and recognition HMM applications for modeling wireless channel parameters.  However, none have been found for recognition of channel dispersion and related conditions such as frequency selectivity and/or time selectivity. Therefore, the authors introduce a mobile wireless channel (MWC) distortion state model (DSM) and a distortion mitigation transform (DMT) linking time-variant non-dispersive, single, or dual-dispersive channel states with effective mitigation methods.  Additionally, the DSM is embedded in a distortion state recognition (DSR) HMM and the CSR testbed for performance verification.  Test results for the DSR algorithm demonstrate the utility of the DSM and the feasibility of CSR.  Accuracy performance results agree with published standard HMM recognition accuracy in terms of sensitivity and specificity.  DSR algorithm limitations are noted and provide direction for future CSR research efforts.

 

Video Shot Boundary Detection – Comparision of Color Histogram and Gist Method

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Video Shot Boundary Detection – Comparision of Color Histogram and Gist Method   

Author Name: P. Swati Sowjanya, Ravi Mishra   

Synopsis:   

Many algorithms have been proposed for detecting video shot boundaries and classifying shot and shot transition types. Here we are using two different methods for comparison, using GIST , Color Histogram. Color histogram method draws the histogram for the frames and detects shot comparing these histograms but this is sensitive to illuminance and motion while the GIST uses two different properties of the video i.e color and gist for the detection of the shots. The aim of this paper is to make a comparison between two of the well-known methods used for detecting video shot boundaries. Firstly various methods are described in the preceding sections then a comparison is made about it. This paper shows that the GIST method produces good result over the other method.

  

Performance Evaluation of AODV and DSDV Routing Protocols Using City Mob in VANETs

Vol.1 No.1

Year: 2012

Issue: Nov-Jan

Title: Performance Evaluation of AODV and DSDV Routing Protocols Using City Mob in VANETs   

Author Name: Sufyan T. Faraj, Yaseen Saleem Yaseen   

Synopsis:   

Routing is one of the most important challenges in Vehicular Ad hoc Networks (VANETs). These networks involve a high cost in the real world experimentation. Thus, simulation is a useful alternative in conducting such a research. In this paper, two important routing protocols (AODV and DSDV) have been considered for testing in VANET environments. Performance evaluation has been accomplished for these two routing protocols using the CityMob mobility generator that generates the required urban mobility scenario files. Then, simulation has been done based on these scenario files using the NS-2 simulator. The performance of the routing protocols has been compared based on some routing metrics (Packet Delivery Ratio and End to End Delay) for different values for the speed of vehicles. The work has been done under Linux operating system.