Papers by Dr.Netra Lokhande
Observations and Analysis of Power Quality Indices Using Custom Power Devices in Power Distribution Network
Lecture notes in networks and systems, Jun 10, 2022
Regular, 2020
Dental radiographs do a great deal of work on the evidence of criminal classification. Science de... more Dental radiographs do a great deal of work on the evidence of criminal classification. Science deontology is used in crimes that deal with the evidence of a person's separation related to dental exposure. Due to the advances in data design and the need to evaluate more cases by legal professionals, it is important to use a human evidence framework. Dental radiographs can be classified as biometric if there are no alternatives to body biometrics, for example, palm, finger, iris, face, leg print, and so on. The human body seen using dental radiographs is best under certain conditions when there are no biometric alternatives because the teeth and bones are treated like skin tissues and tissues found in the human body.
International Journal of Engineering and Advanced Technology, 2019
Hand gesture recognition is challenging task in machine vision due to similarity between inter cl... more Hand gesture recognition is challenging task in machine vision due to similarity between inter class samples and high amount of variation in intra class samples. The gesture recognition independent of light intensity, independent of color has drawn some attention due to its requirement where system should perform during night time also. This paper provides an insight into dynamic hand gesture recognition using depth data and images collected from time of flight camera. It provides user interface to track down natural gestures. The area of interest and hand area is first segmented out using adaptive thresholding and region labeling. It is assumed that hand is the closet object to camera. A novel algorithm is proposed to segment the hand region only. The noise due to ToF camera measurement is eliminated by preprocessing algorithms. There are two algorithms which we have proposed for extracting the hand gestures features. The first algorithm is based on computing the region distance be...
Control of Quadrotor in 2-D for a Commanded Trajectory
2022 2nd Asian Conference on Innovation in Technology (ASIANCON)
Vision-Based Hand Gesture Recognition Techniques using Smartphones
International Journal of Innovative Technology and Exploring Engineering, 2020
In the past few years, the computational performance of smartphone devices has seen tremendous gr... more In the past few years, the computational performance of smartphone devices has seen tremendous growth. Due to which the smartphone has become a suitable platform for various computer-vision based applications which earlier was not possible. In this paper, we study various methods through which we can achieve computer vision-based hand gesture recognition natively on smartphones. If smartphones can support hand gesture recognition it can provide a new way to interact with mobile devices and overcome the hurdles of voice and touch-based user interface improving the user experience at the same time also supports other gesture-based applications. The techniques we study are mainly vision-based since camera module is present on most of the smartphones and it does not require other additional sensors or other hardware. We have compared the various methods available based on algorithms used and corresponding accuracy.
GPOF Registration Based Multi-frame Image Super-Resolution Reconstruction
A robust multi-frame approach of producing a high resolution (HR) image from a sequence of low-re... more A robust multi-frame approach of producing a high resolution (HR) image from a sequence of low-resolution (LR), blurred and noisy images is the purpose of the paper. In the proposed approach, focus is specially on the motion model of Gaussian Pyramid Optical Flow (GPOF) registration which achieves the sub-pixel precision and enables large pixel motions, while keeping the size of the integration window relatively small. The Median “Shift and Add” idea is also introduced to initialize the HR image value in the iterative steps for the optimization of the objective function, when the motions between LR frames are pure translations and the blur is space invariant. Motion estimation is demanding field among researchers. The most general and challenging version of motion estimation is to compute an independent estimate of motion at each pixel, which is generally known as optical or optic flow. In this paper we tackle the correct estimation of the motion vectors by consistently estimating t...
International Journal of Multidisciplinary Research and Development, 2017
Background: An objective measure of nutrition literacy is unavailable for use in the primary care... more Background: An objective measure of nutrition literacy is unavailable for use in the primary care population. The Nutrition Literacy Assessment instrument (NLit) is a tool designed to measure nutrition literacy across six domains and has been previously piloted in breast cancer and parent populations. The purpose of this research was to engage nutrition experts and patients to guide revisions of the NLit for use in adult primary care. Methods: Experts (n = 5) reviewed each item in the NLit using a survey to assign rankings of their agreement according to relevance, clarity, and reading difficulty. Relevance rankings were used to calculate Scale Content Validity Index. After suggested revisions were made, patients (n = 12) were recruited from urban primary care clinics of a University Medical Center located in the Midwestern United States and were interviewed by trained researchers using the cognitive interview approach to generate thoughts, feelings, and ideas regarding NLit items. Data analysis involved qualitative and quantitative methods. Results: Content validity from expert review was confirmed with a total Scale Content Validity Index of 0.90. Themes emerging from the cognitive interviews resulted in changes in the NLit to improve instrument clarity. Conclusion: These data suggest the NLit achieves its target constructs, is understood by the target audience, and is ready to undergo validity and reliability testing within the primary care population.
Range Estimation of Electric Vehicle using MATLAB
Simulation modeling tackles real life problems securely and feasibly. It gives an outstanding str... more Simulation modeling tackles real life problems securely and feasibly. It gives an outstanding strategy for assessment which is effectively checked, passed on and acknowledged. In this paper, dynamic model of an electric vehicle is made with the help of MATLAB Simulink. The energy consumption estimation of the electric vehicle is resolved, compared to the drive cycles related. The impact of various drive cycles on the utilization of energy by vehicle and its consequences for other vehicle boundaries are discussed.
A Comprehensive Study of Different Image Super-Resolution Reconstruction Algorithms
Super-resolution image reconstruction produces a high-resolution image from a set of shifted, blu... more Super-resolution image reconstruction produces a high-resolution image from a set of shifted, blurred, and decimated versions thereof. Super-resolution image restoration has become an active research issue in the field of image restoration. In general, super-resolution image restoration is an ill-posed problem. Prior knowledge about the image can be combined to make the problem well-posed, which contributes to some regularization methods. In these regularization methods, however, regularization parameter was selected by experience in some cases. Other techniques to compute the parameter had too heavy computation cost. This paper presents a generalization of restoration theory for the problem of Super-Resolution Reconstruction (SRR) of an image. In the SRR problem, a set of low quality images is given, and a single improved quality image which fuses their information is required. We present a model for this problem, and show how the classic restoration theory tools- ML, MAP and POCS-...
Novel Image Segmentation Using Particle Swarm Optimization
Data clustering and classification technique algorithms often need to possess enough and prominen... more Data clustering and classification technique algorithms often need to possess enough and prominent number of features in the data. Repeating and dominant features are useful in clustering or segmenting the image. The image segmentation method based on k-mean clustering, hierarchical clustering, and expectation maximization derives the optimum cluster centers based on the number of features such as similar intensity region. Deriving such number optimum number of clusters and its centers is an optimization problem. The aim of this paper is to improve the image segmentation using nature inspired techniques. Image segmentation which is complex optimization problem can be solved by this simple nature inspired PSO (Particle swarm optimization) model which is formulated in this paper. PSO model is generic model which is used to solve number of scientific problems. This paper formulates simple PSO model to solve the image segmentation problem. The proposed algorithm randomly assigns the cen...
Emerging Trends in Engineering Research and Technology Vol. 2
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
The purpose of this paper is to present a computational Analysis of various Artificial Intelligen... more The purpose of this paper is to present a computational Analysis of various Artificial Intelligence based optimization Techniques used to solve OPF problems. The various Artificial Intelligence methods such as Genetic Algorithm(GA), Particle Swarm Optimization(PSO), Bacterial Foraging Optimization(BFO), ANN are studied and analyzed in detail. The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost and transmission loss etc. or maximizes social welfare, load ability etc. while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, power flow limits, output of various compensating devices etc. Traditionally, Classical optimization methods were used effectively to solve optimal power flow. But, recently due to the incorporation of FACTS devices and deregulation of power sector the traditional concepts and practices of power systems are superimposed by an economic m...
Historical Overview: Techniques of Super-Resolution Image Reconstruction
International Journal of Advances in Computing and Information Technology, 2012
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
Super-resolution image reconstruction produces a high-resolution image from a set of shifted, blu... more Super-resolution image reconstruction produces a high-resolution image from a set of shifted, blurred, and decimated versions thereof. Super-resolution image restoration has become an active research issue in the field of image restoration. In general, super-resolution image restoration is an ill-posed problem. Prior knowledge about the image can be combined to make the problem well-posed, which contributes to some regularization methods. In these regularization methods, however, regularization parameter was selected by experience in some cases. Other techniques to compute the parameter had too heavy computation cost. This paper presents a generalization of restoration theory for the problem of Super-Resolution Reconstruction (SRR) of an image. In the SRR problem, a set of low quality images is given, and a single improved quality image which fuses their information is required. We present a model for this problem, and show how the classic restoration theory tools-ML, MAP and POCS-c...
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Papers by Dr.Netra Lokhande