Papers by Dr Papiya Dutta
Detection and Location of Defects Fabrics Using Feature Extraction Technique
This paper presents an approach to automatic detection of fabric defects using digital image proc... more This paper presents an approach to automatic detection of fabric defects using digital image processing. In Textile industry automatic fabric inspection is important to maintain the quality of fabric. Fabric defect detection is carried out manually with human visual inspection for a long time. This paper proposes an approach to recognize fabric defects in textile industry for minimizing production cost and time. Fabric analysis is performed on the basis of digital images of the fabric. The recognizer acquires digital fabric images by image acquisition device and converts that image into binary image by restoration and threshold techniques. This paper introduces a method which reduces the manual work. This image processing technique is done using MATLAB 7.10. This research thus implements a textile defect detector with system vision methodology in image processing.
Designing a cognitive radio with enhancement in throughput and improved spectrum sensing technique
2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE), 2016
An important advantage of cognitive radio is its ability to use the licensed frequency spectrum w... more An important advantage of cognitive radio is its ability to use the licensed frequency spectrum which is being utilized by the primary users. CR has two major roles viz. sensing and throughput optimization. In contrary to conventional methods of sensing viz. cyclostationarity, matched filter detection, maximum to minimum eigen value method etc., spectrum sensing has been improved by implementing Peak vs Average Power Ratio of the received signal in energy detection in the presentation. It has the additional advantages that prior information of the license user is not required and it is free from noise uncertainty. In this paper, the design of the frame for MAC layer has been based on Wireless spectrum Sensing network (WSSN). The access of the channel to the secondary users is done through Handshaking Algorithm. A hybrid frame structure based on CSA and DSA has been devised for the WSSN network and has been implemented which overcomes the drawback of Conventional frame format. The WSSN network removes the sensing time from the Secondary user's frame thereby increasing the transmission time of data and hence the throughput of the system. The cognitive radio frame structure, thus designed in the present paper, improves the throughput of the system and enhance the Spectrum sensing techniques. Finally, the simulation results shows that the proposed method performs better than the conventional method in throughput and provides efficient spectrum sensing technique.
Abstract-In the field of Image handling, amid the transmission and procurement, pictures are adul... more Abstract-In the field of Image handling, amid the transmission and procurement, pictures are adulterated by the diverse sort of commotion. In light of the commotion, nature of picture is diminished and different elements like edge sharpness and example acknowledgment are likewise severely influenced. DWT denoising is done only in detail coefficient, this offer advantage of smoothness and adaption. Reducing noise from single image, natural images, etc. is the challenge for the researchers in digital image processing.in this paper . The denoising methodology uses hybridization of filters & & DWT The denoised signal reconstructed from the remodel can gift various overshoot and undershoot. These peak price don't seem to be contained in original signal itself. they're created by artificial interference in remodel method. to beat the disadvantage mention over HYBRID methodology is employed.
Neural Network Based Object Detection by Utilizing GMM with Histogram Features
Moving object identification and following are the more vital task in video reconnaissance as wel... more Moving object identification and following are the more vital task in video reconnaissance as well as PC vision applications. object recognization is the system of finding the non-stationary substances in the picture successions. Recognition is the initial move towards following the moving item in the video. object action is the following essential stride to track. Here GMM (Gaussian Mixture Model) was used for detection the first step of object detection. While Object representation or action performance is done by training the error back propagation neural network where this trained neural network identify and classify the action of the object as well. Real dataset was used in experiment and comparison was done on different evaluation parameters. It was obtained that proposed work is better as compare to other existing methods. Keywords—Artificial Neural Network, Histogram Feature, Human Action detection, Digital Image processing.
In recent years, the applications of Wireless Sensor Networks (WSNs) have been increased tremendo... more In recent years, the applications of Wireless Sensor Networks (WSNs) have been increased tremendously. In WSNs mechanis m used to enlarge the lifespan of network and provide more efficient functioning procedures that is clustering. Clustering is a procedure to subdivide the sensing field of sensor network into number of clusters. Each cluster selects a leader or hear called cluster head. A cluster head might be elected by the sensor node withinthe cluster or may be pre-assigned by the network administrator. Optimized Clustering can save lot of energy in the network. In our paper we have surveyed various clustering protocols for wireless sensor networks and compared on various parameters like cluster count, cluster size, cluster density, message count, node deployment, heterogeneity of nodes, locationawareness and cluster head selection process etc. In this paper a survey of various popular WSN protocol has been reviewed, majorly LEACH, SEP, HEED & DEEC.
Detection of Faults Using Digital Image Processing Technique
This paper presents an approach to automatic detection of fabric defects using digital image proc... more This paper presents an approach to automatic detection of fabric defects using digital image processing. In Textile industry automatic fabric inspection is important to maintain the quality of fabric. Fabric defect detection is carried out manually with human visual inspection for a long time. This paper proposes an approach to recognize fabric defects in textile industry for minimizing production cost and time. Fabric analysis is performed on the basis of digital images of the fabric. The recognizer acquires digital fabric images by image acquisition device and converts that image into binary image by restoration and threshold techniques. This paper introduces a method which reduces the manual work. This image processing technique is done using MATLAB 7.10. This research thus implements a textile defect detector with system vision methodology in image processing.
In this paper, an improved method based on evolutionary algorithm for speech signal denoising is ... more In this paper, an improved method based on evolutionary algorithm for speech signal denoising is proposed. In this approach, the stochastic global optimization techniques such as Artificial Bee Colony(ABC), Cuckoo Search (CS)algorithm, and Particle Swarm Optimization (PSO) technique are exploited for learning the parameters of adaptive filtering function required for optimum performance. It was found that the ABC algorithm and Cuckoo Search algorithm based speech denoising approach give better performance in terms of signal-to-noise ratio (SNR) as compared to PSO based speech denoising approach. The quantitative (SNR, MSE and Maximum Error (ME)) and visual (Denoised speech signals) results show superiority of the proposed technique over the conventional and state -of-art speech signal denoising techniques. All proposed methods have been simulated in Matlab, and design results are illustrated clearly to show the superiority of the proposed method. Keywords— Adaptive filters, Adaptive...
Utilization of Optical Fibre WDM Channel in Wavelength Routed Networks using Sparse Partial Limited Wavelength Conversion
In the previous 20 years, wavelength conversion has received a considerable attention due to its ... more In the previous 20 years, wavelength conversion has received a considerable attention due to its strong influence on the blocking performance of wavelength-routed WDM networks. In a wavelength-routed WDM network, end users communicate with one another via all-optical WDM channels. In all-optical WDM channels optical fibre is used. Optical fibre is a single, hair-fine filament drawn from molten silica glass. These fibre are replacing metal wire as the transmission medium in high-speed, high-capacity communications systems that convert information into light, which is then transmitted via fibre optic cable. Wavelength converters help to reduce the blocking probability of the network and enhance the fibre utilization. Most of the related works focus on only one aspect of wavelength conversion, i.e., sparse or partial or limited wavelength conversion. This paper will recommend the use of sparse-partial-limited wavelength conversion (SPLWC) integrating all approaches i.e. sparse or parti...
Comparative Analysis of DEEC protocol with Various Energy Efficient Clustering Protocols of WSN’s
Journal of emerging technologies and innovative research, 2017
Palmprint Verification By Proficient Filtering Using Wavelet
Among the various palm print recognition techniques, coding technique is very effective and gives... more Among the various palm print recognition techniques, coding technique is very effective and gives efficient results. In this coding method, gabor filters of four different orientation are convolved with the palm print image to extract the orientation information from the image. The imaginary part of each orientation is added pixel by pixel and then each imaginary palm code is coded into 3 bits. Different wavelet filters are used to improve the accuracy of the system. This scheme is applied in the approximate band. Two different palm prints are matched using angular distance matrices, and db7 wavelet filter gives the equal error rate of 1.1739%, accuracy of 98.84%. Keywords-Discrete wavelet transform, Region of interest, Gabor filter, Euclidean Distance, Equal Error Rate, TSR etc.
Comparison of Metaheuristic Algorithms through Application in Noisy Speech Signal using Adaptive Filtering Approach
An improved method for adaptive noise canceller (ANC) is proposed for noisy speech signal in case... more An improved method for adaptive noise canceller (ANC) is proposed for noisy speech signal in case of random noise. In this approach, ANC is implemented through four different metaheuristic techniques. A comparative study of the performance of various metaheuristic techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Cuckoo Search (CS) and Modified Cuckoo Search (MCS) has been done. Fidelity parameters like signal to noise ratio (SNR) in dB, mean square error (MSE) and maximum error (ME) are observed with varying range of input SNR and it was found that the Modified Cuckoo Search based speech denoising approach give better performance in terms of SNR as compared to other Metaheuristic techniques. The quantitative (SNR, MSE and ME) and visual (Denoised speech signals) results show superiority of the proposed technique over the conventional and state -of-art speech signal denoising techniques. Keywords— Adaptive filters, Adaptive Algorithms, Artificial Bee...
Transmission line fault location using interoperability and integration of data and model
This paper discusses an image denoising technique which employs an SVR (Support Vector Regression... more This paper discusses an image denoising technique which employs an SVR (Support Vector Regression) machine learning technique after performing wavelet transform on the image. Image denoising is an important image processing step in itself and as a pre processing part of some other image processing tasks. The paper proposes an algorithm for removing AWGN from grayscale images. Support Vector (SV) algorithm used here is a supervised learning model and algorithm that analyze data and recognize patterns, used for classification and regression analysis. It is a state of art machine learning algorithm used in pattern and face recognition. SVM is getting popular in image denoising for classification as well as estimation of noisy wavelet coefficients. The wavelet transform forms the basis of almost all signal denoising algorithms, in this paper, 2d Riesz Wavelet transform is used to perform wavelet transform of noisy image, with its monogenic steering property it forms heart of proposed denoising algorithm.
IEEE Transactions on Power Delivery, 1992
UHS refers to operating times ofless thail 5 millisec.on 5 0 Hz power systems. Three d i Ftinct t... more UHS refers to operating times ofless thail 5 millisec.on 5 0 Hz power systems. Three d i Ftinct types of UHS relaying realisation in dis tance protection via advanced generation digital signal processing, possible with cheap and readily available VLSI chips, have been considered. Type I is the correlator detector,Type 11 and-111 are the spectrum and cbpstrum analysers respectively. Performance of these detectors is evaluated with respect to varying system configurations that complicate the post fault signals. Microprocessor implementation of these techniques show that 5 msecs limit is achieved in Type I and I1 detectors whereas Type I11 detector can operate in 3 msecs.
The major challenge in the practical accomplishment of OFDM/SDMA system depends on the efficient ... more The major challenge in the practical accomplishment of OFDM/SDMA system depends on the efficient implemen- tation of a multiuser detection (MUD) technique that separates the spatially multiplexed signal streams. Several algorithms for MIMO detection for spatially-multiplexed signals have been developed till today. The MIMO MUDs that are mostly used in previous research works and practically used are minimum mean squared error (MMSE), decorrelator (ZF), Vertical-Bell laboratories layered space-time (V-BLAST), successive inter- ference cancellation (SIC) and maximum likelihood detection (MLD). MMSE and ZF are linear MIMO detection techniques, while the remaining procedures are non linear techniques. All MUD techniques in general can be explained as a solution to a quadratic optimization problem in most cases. In this work, basic principles of ZF, MMSE, ZF-OSIC, MMSE-OSIC and ML have been explained briefly and a comparison of their performances have been done. Although the detection te...
7th Mediterranean Conference and Exhibition on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2010), 2010
Vehicle-to-building (V2B) provides an option to use the battery energy in electric vehicles to su... more Vehicle-to-building (V2B) provides an option to use the battery energy in electric vehicles to support loads in the power grid. Many researchers have shown that vehicle-togrid (V2G) has many potential benefits. But for various practical reasons wide application of this concept is envisioned on a 5-10 year time horizon. We have focused on V2B as a concept that is practically viable today and may be implemented on a 3-5 year time horizon. This paper aims at demonstrating the potential benefits of Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) as dynamically configurable dispersed energy storage acting at the convergence of transportation and power system. A new parking facility as an energy exchange station called "smart garage" is discussed in this paper. Based on the availability analysis of smart garages, the benefits of using BEVs/PHEVs as energy storage for demand side management (DSM) and outage management (OM) are discussed in detail. A strategy to adopting BEVs/PHEV uses in the V2B mode under the peak load and outage condition is studied and demonstrated with test cases.
2012 IEEE Power and Energy Society General Meeting, 2012
He is also a Deputy Director of another NSF I/UCRC "Electrical Vehicles: Transportation and Elect... more He is also a Deputy Director of another NSF I/UCRC "Electrical Vehicles: Transportation and Electricity Convergence, EV-TEC". His main research interests are digital simulators and simulation methods for relay testing, as well as application of intelligent methods to power system monitoring, control, and protection. He has published over 400 papers, given over 100 seminars, invited lectures and short courses, and consulted for over 50 companies worldwide. He is the Principal of Test Laboratories International, a consulting firm specializing in automated fault analysis and IED testing. Dr.
2012 45th Hawaii International Conference on System Sciences, 2012
The concept of interoperability of data and model as presented in this paper is viewed as being v... more The concept of interoperability of data and model as presented in this paper is viewed as being very useful for implementing variety of future applications related to power system monitoring, protection, control and operation. To illustrate the proposed concept, two applications are used: state estimation and fault location. Generalized State Estimators (GSEs) consider both measurements and switching device statuses as variables to be estimated. We propose a unified generalized state estimator that uses only one class of network objects (node-breaker), which would avoid model conversions, enables unified topology processing, and supports flexible forms of generalized estimation. The proposed Fault Location (FL) application uses different types of measured data which utilizes power system static data modeled using bus-branch. Significant number of mappings is required to correlate the measured data and model. It is shown that both applications will be simplified if unified generalized representation of data and model as suggested in this paper is utilized.
This paper presents a simulation test bed aimed at evaluation of relay operation under faults lea... more This paper presents a simulation test bed aimed at evaluation of relay operation under faults leading to cascading events. The test bed uses physical relays and waveforms replayed from the Alternative Transients Program (ATP) simulations. A system level tool which identifies probable cascade scenarios for the given load condition and topology is presented. These scenarios are analyzed for zone-3 misoperation on any of the overloaded lines which may lead to cascading events. The fault scenarios are simulated in ATP and the generated wave forms are used to test operation of actual relays. The relay operation evaluation has been performed using SEL 421 distance relay utilizing an open-loop transient testing simulator. The IEEE 118 bus system is used for creating test cases.
2011 North American Power Symposium, 2011
Traditional transmission line fault location methods require measurements from at least one end o... more Traditional transmission line fault location methods require measurements from at least one end of the faulted line. Measurements from all the ends of the faulted line are desirable but not always available. Sparse measurement based fault location scheme using phasor measurements from different substations located in the vicinity where the fault has occurred can be applied if the measurements are not available from any of the line ends. Fault resistance is one of the major sources of uncertainty in transmission line fault location estimation. This paper presents a correction scheme to reduce impact of fault resistance on sparse measurement method.
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Papers by Dr Papiya Dutta