Digital video magnification is a computer-based microscope, which is useful to detect subtle changes to human eyes in recorded videos. This technology can be employed in several areas such as medical, biological, mechanical and physical applications. Eulerian is the most popular approach in video magnification. However, amplifying the subtle changes in video produces amplifying the subtle noise. This paper proposes an approach to reduce amplified noise in magnified video for both type of changes amplifications, color and motion. The proposed approach processes the resulted video from Eulerian algorithm whether linear or phase based in order to noise cancellation. The approach utilizes wavelet denoising method to localize the frequencies of distributed noise over the different frequency bands. Subsequently, the energy of the coefficients under localized frequencies are attenuated by attenuating the amplitude of these coefficients. The experimental results of the proposed approach show its superiority over conventional linear and phase based Eulerian video magnification approaches in terms of quality of the resulted magnified videos. This allows to amplify the videos by larger amplification factor, so that several new applications can be added to the list of Eulerian video magnification users. Furthermore, the processing time does not significantly increase, the increment is only less than 3% of the overall processing compare to conventional Eulerian video magnification.
Developed approach for phase-based Eulerian video magnificationTELKOMNIKA JOURNAL
This paper proposes a modification approach for phased-based EVM in order to reduce the processing time without effect the quality of the magnified video. The proposed approach applies a resizing process on the input video using Lanczos-3 algorithm. Then, it decomposes video frames using steerable pyramid to obtain multi-scale frame with its orientation. Subsequently, the resulted frames are filtered by temporal filters for specific bands and the filtered frames are multiplied by a magnification factor. Now, both the magnified regions and the unmagnified regions for each frame are added together. Finally, reconstructing the produced magnified multi-scale frames using the inverse steerable pyramid. The experimental results show that superiority of the proposed approach compares to the conventional phase-based EVM in processing time, where the processing time reduction about 60-65%. Furthermore, this approach does not affect on the video quality, which maintain it in the boundary of the conventional Phase-based EVM.
Comparative Analysis of Dispersion Compensating Fiber (DCF) and Multiple Opti...rahulmonikasharma
Optical communication when used for long haul communication is characterized by dispersion and nonlinearities. Different techniques are used for the dispersion compensation and nonlinearity mitigation. Two of these techniques are Dispersion Compensating Fiber (DCF) and Optical Phase Conjugation (OPC). In this paper the performance of the system is analyzed by comparing various results at the receiver. A 10Gb/s NRZ signal is launched into a long Single Mode Fiber (SMF). Results in the terms of Q-factor (linear) and BER are observed by varying fiber length. Optical system consisting of one OPC and two OPC is also analyzed for different transmission distance. Simulation results show that, when compared with optical system consisting of one OPC, Q-factor improvement of 3.51 is achieved for the optical system consisting of two OPC. Nonlinearities are mitigated using DCF and OPC and on comparing with DCF, Q-factor improvement of 11.3 is achieved for OPC.
Automation of DMPS Manufacturing by Using LabView and PLC IJECEIAES
This Paper is to enable the Siemens (Programmable Logic Control) CPU 313-5A to communicate with the Lab VIEW and to control the process accuracy by image processing. The communication between CPU 313-5A and Lab VIEW is via OPC (OLE for Process Control). Process Accuracy is achieved with the use of Labview Image Processing and Gray Scale matching Pattern. Accuracy in the gray scale matching will purely depend on the calibration of the camera with respect to the corresponding image. The digital output from the labview is communicated to PLC via Ethernet Protocol for the industrial process control. With the use of Labview the dead time while using the normal image vision module in PLC can be minimized. Labview uses the gray scale matching technique which is more accurate than the normal image vision module used in PLC.
Developed approach for phase-based Eulerian video magnificationTELKOMNIKA JOURNAL
This paper proposes a modification approach for phased-based EVM in order to reduce the processing time without effect the quality of the magnified video. The proposed approach applies a resizing process on the input video using Lanczos-3 algorithm. Then, it decomposes video frames using steerable pyramid to obtain multi-scale frame with its orientation. Subsequently, the resulted frames are filtered by temporal filters for specific bands and the filtered frames are multiplied by a magnification factor. Now, both the magnified regions and the unmagnified regions for each frame are added together. Finally, reconstructing the produced magnified multi-scale frames using the inverse steerable pyramid. The experimental results show that superiority of the proposed approach compares to the conventional phase-based EVM in processing time, where the processing time reduction about 60-65%. Furthermore, this approach does not affect on the video quality, which maintain it in the boundary of the conventional Phase-based EVM.
Comparative Analysis of Dispersion Compensating Fiber (DCF) and Multiple Opti...rahulmonikasharma
Optical communication when used for long haul communication is characterized by dispersion and nonlinearities. Different techniques are used for the dispersion compensation and nonlinearity mitigation. Two of these techniques are Dispersion Compensating Fiber (DCF) and Optical Phase Conjugation (OPC). In this paper the performance of the system is analyzed by comparing various results at the receiver. A 10Gb/s NRZ signal is launched into a long Single Mode Fiber (SMF). Results in the terms of Q-factor (linear) and BER are observed by varying fiber length. Optical system consisting of one OPC and two OPC is also analyzed for different transmission distance. Simulation results show that, when compared with optical system consisting of one OPC, Q-factor improvement of 3.51 is achieved for the optical system consisting of two OPC. Nonlinearities are mitigated using DCF and OPC and on comparing with DCF, Q-factor improvement of 11.3 is achieved for OPC.
Automation of DMPS Manufacturing by Using LabView and PLC IJECEIAES
This Paper is to enable the Siemens (Programmable Logic Control) CPU 313-5A to communicate with the Lab VIEW and to control the process accuracy by image processing. The communication between CPU 313-5A and Lab VIEW is via OPC (OLE for Process Control). Process Accuracy is achieved with the use of Labview Image Processing and Gray Scale matching Pattern. Accuracy in the gray scale matching will purely depend on the calibration of the camera with respect to the corresponding image. The digital output from the labview is communicated to PLC via Ethernet Protocol for the industrial process control. With the use of Labview the dead time while using the normal image vision module in PLC can be minimized. Labview uses the gray scale matching technique which is more accurate than the normal image vision module used in PLC.
Online video-based abnormal detection using highly motion techniques and stat...TELKOMNIKA JOURNAL
At the essence of video surveillance, there are abnormal detection approaches, which have been proven to be substantially effective in detecting abnormal incidents without prior knowledge about these incidents. Based on the state-of-the-art research, it is evident that there is a trade-off between frame processing time and detection accuracy in abnormal detection approaches. Therefore, the primary challenge is to balance this trade-off suitably by utilizing few, but very descriptive features to fulfill online performance while maintaining a high accuracy rate. In this study, we propose a new framework, which achieves the balancing between detection accuracy and video processing time by employing two efficient motion techniques, specifically, foreground and optical flow energy. Moreover, we use different statistical analysis measures of motion features to get robust inference method to distinguish abnormal behavior incident from normal ones. The performance of this framework has been extensively evaluated in terms of the detection accuracy, the area under the curve (AUC) and frame processing time. Simulation results and comparisons with ten relevant online and non-online frameworks demonstrate that our framework efficiently achieves superior performance to those frameworks, in which it presents high values for the accuracy while attaining simultaneously low values for the processing time.
MULTI WAVELET BASED IMAGE COMPRESSION FOR TELE MEDICAL APPLICATIONprj_publication
Analysis and compression of medical image is an important area of biomedical
engineering. Analysis of medical image and data compression are rapidly evolving field with
growing applications in the teleradiology, Bio-medical, tele-medicine and medical data
analysis. Wavelet based techniques are latest development in the field of medical image
compression. The ROI must be compressed by a Lossless or a near lossless compression
algorithm. Wavelet based techniques are most recent growth in the area of medical image
compression.
Wavelet multi-resolution decomposition of images has shown its efficiency in many
image processing areas and specifically in compression. Transformed coefficients are
obtained by expanding a signal on a wavelet basis. The transformed signal is a different
representation of the same underlying data. Such representation is efficient if a relevant part
of the original information is found in a relative small number of coefficients. In this sense,
wavelets are near optimal bases for a wide class of signals with some smoothness, which is
the reason for compression.
Keywords: Image compression, Integer Multiwavelet Transform.
1. INTRODUCTION
Image Compression is used to reduce the number of bits required to represent an
image or a video sequence. A Compression algorithm takes an input X and generates
compressed information that requires fewer bits. The Decompression algorithm reconstructs
the compressed information and gives the original.
A compression of medical image is an important area of biomedical and telemedici
An Application of Second Generation Wavelets for Image Denoising using Dual T...IDES Editor
The lifting scheme of the discrete wavelet transform
(DWT) is now quite well established as an efficient technique
for image denoising. The lifting scheme factorization of
biorthogonal filter banks is carried out with a linear-adaptive,
delay free and faster decomposition arithmetic. This adaptive
factorization is aimed to achieve a well transparent, more
generalized, complexity free fast decomposition process in
addition to preserve the features that an ordinary wavelet
decomposition process offers. This work is targeted to get
considerable reduction in computational complexity and power
required for decomposition. The hard striking demerits of
DWT structure viz., shift sensitivity and poor directionality
had already been proven to be washed out with an emergence
of dual tree complex wavelet (DT-CWT) structure. The well
versed features of DT-CWT and robust lifting scheme are
suitably combined to achieve an image denoising with prolific
rise in computational speed and directionality, also with a
desirable drop in computation time, power and complexity of
algorithm compared to all other techniques.
Geometric wavelet transform for optical flow estimation algorithmijcga
This paper described an algorithm for computing the optical flow (OF) vector of a moving objet in a video sequence based on geometric wavelet transform (GWT). This method tries to calculate the motion between two successive frames by using a GWT. It consists to project the OF vectors on a basis of geometric wavelet. Using GWT for OF estimation has been attracting much attention. This approach takes advantage of the geometric wavelet filter property and requires only two frames. This algorithm is fast and able to estimate the OF with a low-complexity. The technique is suitable for video compression, and can be used for stereo vision and image registration.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Digital image enhancement by brightness and contrast manipulation using Veri...IJECEIAES
A foggy environment may cause digitally captured images to appear blurry, dim, or low in contrast. This will impact computer vision systems that rely on image information. With the need for real-time image information, such as a plate number recognition system, a simple yet effective image enhancement algorithm using a hardware implementation is very much needed to fulfil the need. To improve images that suffer from low exposure and hazy, the hardware implementations are usually based on complex algorithms. Hence, the aim of this paper is to propose a less complex enhancement algorithm for hardware implementation that is able to improve the quality of such images. The proposed method simply combines brightness and contrast manipulation to enhance the image. In order to see the performance of the proposed method, a total of 100 vehicle registration number images were collected, enhanced, and evaluated. The evaluation results were compared to two other enhancement methods quantitatively and qualitatively. Quantitative evaluation is done by evaluating the output image using peak signal-to-noise ratio and mean-square error evaluation metrics, while a survey is done to evaluate the output image qualitatively. Based on the quantitative evaluation results, our proposed method outperforms the other two enhancement methods.
Embedded Implementations of Real Time Video Stabilization Mechanisms A Compre...YogeshIJTSRD
Video Stabilization has been widely researched and still is under active research considering the advancements that are being done in the field of digital imagery. Despite all the works, Hardware based Real time Video Stabilization systems especially works dealing with implementation of Technology on prototype Implementation boards have been very few. This review works focuses on the specific aspect of the modern day Stabilization systems implemented in prototyping boards and the algorithms that have been found suitable for such implementation taking considerations of cost, size and speed as the principal criterions. Mohammed Ahmed | Dr. Laxmi Singh "Embedded Implementations of Real Time Video Stabilization Mechanisms: A Comprehensive Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39963.pdf Paper URL: https://www.ijtsrd.com/engineering/other/39963/embedded-implementations-of-real-time-video-stabilization-mechanisms-a-comprehensive-review/mohammed-ahmed
Intensify Denoisy Image Using Adaptive Multiscale Product ThresholdingIJERA Editor
This Paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. This paper proposed a method based on image de-noising and edge enhancement of noisy multidimensional imaging data sets. Medical images are generally suffered from signal dependent noises i.e. speckle noise and broken edges. Most of the noises signals appear from machine and environment generally not contribute to the tissue differentiation. But, the noise generated due to above mentioned reason causes a grainy appearance on the image, hence image enhancement is required. For the intent of image denoising, Adaptive Multiscale Product Thresholding based on 2-D wavelet transform is used. In this method, contiguous wavelet sub bands are multiplied to improve edge structure while reducing noise. In multiscale products, boundaries can be successfully distinguished from noise. Adaptive threshold is designed and forced on multiscale products as an alternative of wavelet coefficients or recognize important features. For the edge enhancement. Canny Edge Detection Algorithm is used with scale multiplication technique. Simulation results shows that the planned technique better suppress the Poisson noise among several noises i.e. salt & pepper, speckle noise and random noise. The Performance of Image Intesification can be estimate by means of PSNR, MSE.
Intensify Denoisy Image Using Adaptive Multiscale Product ThresholdingIJERA Editor
This Paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. This paper proposed a method based on image de-noising and edge enhancement of noisy multidimensional imaging data sets. Medical images are generally suffered from signal dependent noises i.e. speckle noise and broken edges. Most of the noises signals appear from machine and environment generally not contribute to the tissue differentiation. But, the noise generated due to above mentioned reason causes a grainy appearance on the image, hence image enhancement is required. For the intent of image denoising, Adaptive Multiscale Product Thresholding based on 2-D wavelet transform is used. In this method, contiguous wavelet sub bands are multiplied to improve edge structure while reducing noise. In multiscale products, boundaries can be successfully distinguished from noise. Adaptive threshold is designed and forced on multiscale products as an alternative of wavelet coefficients or recognize important features. For the edge enhancement. Canny Edge Detection Algorithm is used with scale multiplication technique. Simulation results shows that the planned technique better suppress the Poisson noise among several noises i.e. salt & pepper, speckle noise and random noise. The Performance of Image Intesification can be estimate by means of PSNR, MSE.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
More Related Content
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Online video-based abnormal detection using highly motion techniques and stat...TELKOMNIKA JOURNAL
At the essence of video surveillance, there are abnormal detection approaches, which have been proven to be substantially effective in detecting abnormal incidents without prior knowledge about these incidents. Based on the state-of-the-art research, it is evident that there is a trade-off between frame processing time and detection accuracy in abnormal detection approaches. Therefore, the primary challenge is to balance this trade-off suitably by utilizing few, but very descriptive features to fulfill online performance while maintaining a high accuracy rate. In this study, we propose a new framework, which achieves the balancing between detection accuracy and video processing time by employing two efficient motion techniques, specifically, foreground and optical flow energy. Moreover, we use different statistical analysis measures of motion features to get robust inference method to distinguish abnormal behavior incident from normal ones. The performance of this framework has been extensively evaluated in terms of the detection accuracy, the area under the curve (AUC) and frame processing time. Simulation results and comparisons with ten relevant online and non-online frameworks demonstrate that our framework efficiently achieves superior performance to those frameworks, in which it presents high values for the accuracy while attaining simultaneously low values for the processing time.
MULTI WAVELET BASED IMAGE COMPRESSION FOR TELE MEDICAL APPLICATIONprj_publication
Analysis and compression of medical image is an important area of biomedical
engineering. Analysis of medical image and data compression are rapidly evolving field with
growing applications in the teleradiology, Bio-medical, tele-medicine and medical data
analysis. Wavelet based techniques are latest development in the field of medical image
compression. The ROI must be compressed by a Lossless or a near lossless compression
algorithm. Wavelet based techniques are most recent growth in the area of medical image
compression.
Wavelet multi-resolution decomposition of images has shown its efficiency in many
image processing areas and specifically in compression. Transformed coefficients are
obtained by expanding a signal on a wavelet basis. The transformed signal is a different
representation of the same underlying data. Such representation is efficient if a relevant part
of the original information is found in a relative small number of coefficients. In this sense,
wavelets are near optimal bases for a wide class of signals with some smoothness, which is
the reason for compression.
Keywords: Image compression, Integer Multiwavelet Transform.
1. INTRODUCTION
Image Compression is used to reduce the number of bits required to represent an
image or a video sequence. A Compression algorithm takes an input X and generates
compressed information that requires fewer bits. The Decompression algorithm reconstructs
the compressed information and gives the original.
A compression of medical image is an important area of biomedical and telemedici
An Application of Second Generation Wavelets for Image Denoising using Dual T...IDES Editor
The lifting scheme of the discrete wavelet transform
(DWT) is now quite well established as an efficient technique
for image denoising. The lifting scheme factorization of
biorthogonal filter banks is carried out with a linear-adaptive,
delay free and faster decomposition arithmetic. This adaptive
factorization is aimed to achieve a well transparent, more
generalized, complexity free fast decomposition process in
addition to preserve the features that an ordinary wavelet
decomposition process offers. This work is targeted to get
considerable reduction in computational complexity and power
required for decomposition. The hard striking demerits of
DWT structure viz., shift sensitivity and poor directionality
had already been proven to be washed out with an emergence
of dual tree complex wavelet (DT-CWT) structure. The well
versed features of DT-CWT and robust lifting scheme are
suitably combined to achieve an image denoising with prolific
rise in computational speed and directionality, also with a
desirable drop in computation time, power and complexity of
algorithm compared to all other techniques.
Geometric wavelet transform for optical flow estimation algorithmijcga
This paper described an algorithm for computing the optical flow (OF) vector of a moving objet in a video sequence based on geometric wavelet transform (GWT). This method tries to calculate the motion between two successive frames by using a GWT. It consists to project the OF vectors on a basis of geometric wavelet. Using GWT for OF estimation has been attracting much attention. This approach takes advantage of the geometric wavelet filter property and requires only two frames. This algorithm is fast and able to estimate the OF with a low-complexity. The technique is suitable for video compression, and can be used for stereo vision and image registration.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Digital image enhancement by brightness and contrast manipulation using Veri...IJECEIAES
A foggy environment may cause digitally captured images to appear blurry, dim, or low in contrast. This will impact computer vision systems that rely on image information. With the need for real-time image information, such as a plate number recognition system, a simple yet effective image enhancement algorithm using a hardware implementation is very much needed to fulfil the need. To improve images that suffer from low exposure and hazy, the hardware implementations are usually based on complex algorithms. Hence, the aim of this paper is to propose a less complex enhancement algorithm for hardware implementation that is able to improve the quality of such images. The proposed method simply combines brightness and contrast manipulation to enhance the image. In order to see the performance of the proposed method, a total of 100 vehicle registration number images were collected, enhanced, and evaluated. The evaluation results were compared to two other enhancement methods quantitatively and qualitatively. Quantitative evaluation is done by evaluating the output image using peak signal-to-noise ratio and mean-square error evaluation metrics, while a survey is done to evaluate the output image qualitatively. Based on the quantitative evaluation results, our proposed method outperforms the other two enhancement methods.
Embedded Implementations of Real Time Video Stabilization Mechanisms A Compre...YogeshIJTSRD
Video Stabilization has been widely researched and still is under active research considering the advancements that are being done in the field of digital imagery. Despite all the works, Hardware based Real time Video Stabilization systems especially works dealing with implementation of Technology on prototype Implementation boards have been very few. This review works focuses on the specific aspect of the modern day Stabilization systems implemented in prototyping boards and the algorithms that have been found suitable for such implementation taking considerations of cost, size and speed as the principal criterions. Mohammed Ahmed | Dr. Laxmi Singh "Embedded Implementations of Real Time Video Stabilization Mechanisms: A Comprehensive Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39963.pdf Paper URL: https://www.ijtsrd.com/engineering/other/39963/embedded-implementations-of-real-time-video-stabilization-mechanisms-a-comprehensive-review/mohammed-ahmed
Intensify Denoisy Image Using Adaptive Multiscale Product ThresholdingIJERA Editor
This Paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. This paper proposed a method based on image de-noising and edge enhancement of noisy multidimensional imaging data sets. Medical images are generally suffered from signal dependent noises i.e. speckle noise and broken edges. Most of the noises signals appear from machine and environment generally not contribute to the tissue differentiation. But, the noise generated due to above mentioned reason causes a grainy appearance on the image, hence image enhancement is required. For the intent of image denoising, Adaptive Multiscale Product Thresholding based on 2-D wavelet transform is used. In this method, contiguous wavelet sub bands are multiplied to improve edge structure while reducing noise. In multiscale products, boundaries can be successfully distinguished from noise. Adaptive threshold is designed and forced on multiscale products as an alternative of wavelet coefficients or recognize important features. For the edge enhancement. Canny Edge Detection Algorithm is used with scale multiplication technique. Simulation results shows that the planned technique better suppress the Poisson noise among several noises i.e. salt & pepper, speckle noise and random noise. The Performance of Image Intesification can be estimate by means of PSNR, MSE.
Intensify Denoisy Image Using Adaptive Multiscale Product ThresholdingIJERA Editor
This Paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. This paper proposed a method based on image de-noising and edge enhancement of noisy multidimensional imaging data sets. Medical images are generally suffered from signal dependent noises i.e. speckle noise and broken edges. Most of the noises signals appear from machine and environment generally not contribute to the tissue differentiation. But, the noise generated due to above mentioned reason causes a grainy appearance on the image, hence image enhancement is required. For the intent of image denoising, Adaptive Multiscale Product Thresholding based on 2-D wavelet transform is used. In this method, contiguous wavelet sub bands are multiplied to improve edge structure while reducing noise. In multiscale products, boundaries can be successfully distinguished from noise. Adaptive threshold is designed and forced on multiscale products as an alternative of wavelet coefficients or recognize important features. For the edge enhancement. Canny Edge Detection Algorithm is used with scale multiplication technique. Simulation results shows that the planned technique better suppress the Poisson noise among several noises i.e. salt & pepper, speckle noise and random noise. The Performance of Image Intesification can be estimate by means of PSNR, MSE.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
An Approach to Detecting Writing Styles Based on Clustering Techniquesambekarshweta25
An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4701 - 4711
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technique based on the Eulerian perspective. The technique has named Eulerian video magnification (EVM)
and becomes one of the standards that used in video magnification. The method is used to track liquid voxel
properties such as speed and pressure that evolve over time.
Two main types EVM are existed depend on the method of multiple scale decomposition, linear
based and phase based. In linear-based EVM (LB-EVM) [6], Laplacian pyramid decomposition method is
applied to analyse a source video into multiple-spatial scales, followed by the temporal filter of the specific
frequency bands. The outputs of the temporal filter are then amplified by increasing the energy using
magnification factor and added back to the original decomposed. Finally, the processed frames are
reconstructed by collapse of the Laplacian pyramid. Although LB-EVM succeeds in amplifying motion and
colour changes in video clips and eliminates the need for a costly optical flow calculation [5], it supports
small magnification factors at high spatial frequencies and increases the noise level linearly as
the magnification factor increases. In addition, during a colour is magnify, some unwanted movement also
magnified. To solve LB-EVM problems, Wadhwa et al. [7] have proposed a new Eulerian method, based
on complex steerable pyramids [8], which is phase-based optical flow methods [9]. The phase-based
EVM (PB-EVM) method supports larger magnification factors. However, it is more complex than LB-EVM,
so that it requires significant longer time to implement than LB-EVM. In general, the acceptable accuracy of
EVM helps to employing it in several applications such as material engineering, mechanical engineering,
human health care and so on [10–12].
In order to reduce execution time, a new pyramid in [13, 14], which is called the Riesz pyramid
Liu et al. [15] proposed a way to improve LB-EVM after processing, which is called enhanced EVM
(E2VM). The efficient motion magnification system (EMMS) method has been developed to improve
processing speed [16], which depends on wavelet decomposition. This method improves the speed of
implementation and reduces noise. However, it supports only relatively small magnification factor.
This paper proposes an enhanced approach for LB-EVM and PB-EVM in order to reduce
significantly the noise of the magnified video. Also the proposed approaches can attenuate the unwanted
subtle motion in case of colour magnification. The proposed method superior in terms of magnified video
quality compare to conventional EVM methods. The proposed work uses a wavelet transform to detect and
remove noise from the magnified video frames.
The rest of the paper is organized as: section 2 provides background information about LB-EVM
and PB-EVM. Also, the principles of denosing based wavelet are described briefly. Section 3 explains
the proposed approach. The simulation results and discussion are given in Section 4. Finally, conclusions
are presented in section 5.
2. BACKGROUND
2.1. Linear-based Eulerian video magnification
The small movement amplification can be achieved through computer processing [5, 17] based
optical flow by temporal processing using Taylor first-order series extensions [18]. This technique named
LB-EVM and it is linear processing. In this technique, the input video frames decompose into multiple
spatial bands using the entire Laplaceian pyramid [6, 19, 20]. The Laplacian pyramid is a data structure
where the size of the image is downsampled in successive sporadic density, until so there is no additional
downsampling possible. The temporal filter is then applied to extract the interest frequency bands to be
amplified and then multiply by the desired magnification factor. Subsequently, the magnified bands are
combined with the frames that are entered to the temporal filter. Finally, the resulted magnified frames are
reconstructed by retrieving the original scale from the multiple scales.
The basic disadvantage of this method is the failing with increasing magnification factor. This is
because the original noise increases linearly with increasing magnification factor [21]. Thus, this method is
efficient in magnifying colour changes when the magnification factor is small. Figure 1 shows the working
mechanism of LB-EVM.
2.2. Phase-based Eulerian video magnification
LB-EVM supports relatively small magnification factors, which can greatly amplify noise when
increasing the magnification factor. As a result of these reasons, the method of motion processing was
developed in [7] and is based on complex steerable technique [8, 9, 22]. PB-EVM is inspired by motion
without movement [23] and phase-based optical flow [9]. The basic functions of the transform are similar to
Gabor wavelets [24].
This phase-based technique improves the LB-EVM method, it supports larger magnification and has
much better noise performance. Because the linear method amplifies changes in the temporal brightness,
the noise amplitude is amplified linearly. In contrast, this method modifies the phase, not the amplitudes,
3. Int J Elec & Comp Eng ISSN: 2088-8708
Efficient denoising approach based Eulerian video magnification for colour... (Haider Ismael Shahadi)
4703
which do not increase the amplitude of spatial noise linearly. This method that it increases the differences in
phase by the magnification factor that can amplify hidden movements. These pyramids rely on Fourier
analysis to analyze the image into sub-domains and phase. The main drawback in this method is the long
processing time [21]. Figure 2 shows the working mechanism of PB-EVM [7].
Figure 1. Overall structure of the linear-based-EVM [6]
Figure 2. General structure of phase-based EVM
2.3. Wavelet denoising methods
In order to reduce noise of EVM, wavelet base denosing is used in this paper. The process of image
de-noising by wavelet, consists of the following main stages: 1) wavelet transform, 2) Estimate a threshold,
3) apply the threshold, and 4) inverse wavelet transform. Figure 3 shows the block diagram of the wavelet
denoising method.
Figure 3. Block diagram of wavelet denoising transform
An image can be decomposed into several frequency bands by wavelet transform. Wavelet
transform converts frequency signal information that shows coefficients which distributed in horizontal,
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vertical, and diagonal parts of the image. The original image is divided into four elements: LL, HL, LH, and
HH through the application of horizontal and vertical filters. The sub-band gives the LL approximately or
the average of the original image. The other three sub-bands are details representing wavelet coefficients.
The HL1, HH1, and LH1 subdomains represent the detail coefficients, while the LL1 sub-band denotes
low-level coefficients [25, 26]. The two-dimensional decomposition of the wavelet transform is achieved
by additional decomposition of the LL1 sub-band as shown in Figure 4. By determining the thresholding
of these detailed wavelet coefficients, the image de-noising is accomplished while maintaining its
fundamental features.
(a) (b)
Figure 4. Wavelet decomposition for 2D image (a) one-level and (b) two-levels decomposition
After decomposition, it is subject to the wavelet threshold that will select and analyze the specific
wavelet coefficients. Wavelet threshold is a technique for estimating the signal that takes advantage of
wavelet transform possibilities to de-noising the signal. The basic threshold types are hard and soft
thresholding. In hard threshold, the wavelet coefficients are reset to zero if they are less than threshold level,
and remain as it is in otherwise [27]. In this method many artificial noise points are produced at the edges of
the images, resulting in image distortion. The new wavelet coefficient values (Cn) are determined by (1) that
set to original coefficient values (C) if these values greater than the threshold (ε) and set to zeros otherwise.
𝐶 𝑛 = {
𝐶 𝑖𝑓 |𝐶| > 𝜀
0 𝑖𝑓 |𝐶| < 𝜀
(1)
In soft threshold, the thresholds produce based on a visually interesting of the image [28]. It can
overcome the shortcomings of the hard threshold algorithm. So the results processed relatively smoothly.
Soft threshold function is given by (2):
𝐶 𝑛 = {
𝑠𝑔𝑛(𝐶) × (𝐶 − 𝜀) 𝑖𝑓 𝐶 > 𝜀
0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
(2)
In our proposed method, the soft threshold method is used to analyze the performance of
the denoising system for different levels of DWT decomposition, because of the soft threshold leads to a less
severe distortion of the object of interest than the other thresholds techniques. Finally, the inverse wavelet
conversion is done to obtain the reconstructed image.
3. PROPOSED APPROACH
This section illustrates the overall proposed approach. The approach utilizes the same algorithm of
the conventional LB-EVM and PB-EVM. However, an important post-processing stage is added in such
a way to overcome the problem of noise magnification in the magnified video frames. This is results
a significant improvement in the quality of the magnified video. The steps of the proposed approach are
as follows.
The video file is read as AVI format, then converting all video frames from RGB space into NTSC
(or YIQ) space. The Y component denotes the information of illumination; I and Q denote the information
of the chrominance. The YIQ colour system is aim to benefit advantage of human response characteristics to
the colors. This step is done by applying (3) on all the frame of the video.
[
𝑌
𝐼
𝑄
] = [
0.299 0.587 0.114
0.596 −0.274 −0.322
0.211 −0.523 0.312
] [
𝑅
𝐺
𝐵
] (3)
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The next step is applying the spatial filter. For LB-EVM method, the Laplacian pyramid
decomposition is applied on Y-layer for each video frame in order to decompose the source frames in
different spatial bands. While in PB-EVM the steerable pyramid decomposition is applied on each layer
(Y, I, and Q) of the video frames individually. The decomposition is used in order to factorize the video
frames into scalable images for different levels of decomposition. The steerable pyramid [8] is a transform
that analyzes an image based on spatial scale, orientation, and position.
The resulted bands from the previous step entered to temporal filter to pass only the interest bands
of frequencies for amplifying. Subsequently, amplification process is applied on the filtered frames. This is
attained by multiplying the result frequencies band from the temporal filter by the amplification factor.
Then, the amplified filtered frames combine with the unfiltered frames. In order to reduce the amplified noise
in each resulted frame from the previous stage, the denoising process based wavelet is applied. Daubechies
type 4 is used as a wavelet function with five level of decomposition and soft threshold is applied in denosing
stage. Finally, Laplacian or Steerable pyramid reconstruction is applied on the denoised frames depending of
the type LB-EVM or PB-EVM and converted the reconstructed magnified frames from YIQ space into RGB
space to obtain the original colour of video. This step is done by applying (4) on all the frame of the video.
[
𝑅
𝐺
𝐵
] = [
1 0.956 0.619
1 −0.272 −0.647
1 −1.106 1.703
] [
𝑌
𝐼
𝑄
] (4)
Finally, we get the final video after processing. Figure 5 shows the working mechanism of proposed approach.
Figure 5. The proposed approach based-EVM
4. RESULTS AND DISCUSSION
This section presents the experimental results of the proposed approach to enhance noise
performance for both LB-EVM and PB-EVM approach and compares them to the results of the conventional
LB-EVM and PB-EVM approaches. These experiments are achieved in Matlab software version 2017-b.
Five source videos are used in our tests that are shown in Figure 5. All the used videos in our tests have
an AVI format. The tested videos that are shown in Figure 5 include: the baby with dimension 960×544×3,
number of frames is 301 frame, and a frame rate of 30 fps, the eye with dimension 1152×896×3, number of
frames is 120 frame, and a frame rate of 500 fps, the camera with a dimension 512×384×3, number of frames
is 1001 frame, and a frame rate of 300 fps, the face with dimension 528×592×3, number of frames is
301 frame, and a frame rate of 30 fps and finally, the guitar with dimension 432×192×3 , number of frames is
300 frame, and a frame rate of 600 fps. In order to verify the superiority of the proposed approach over
the conventional approaches in terms of video quality, we measure the measure the magnified video quality
and execution time for both of the proposed and conventional approaches using the same computer and
the input videos. In order to measure the video quality, several evaluated functions are used, which include
the following.
a. Peak signal-to-noise ratio (PSNR): The measurement is achieved according to (5) by dividing the square
of maximum pixel intensity over the mean square error of each video frame. Subsequently, the average
value of the PSNR of the entire video frames is calculated to get the final required PSNR:
𝑃𝑁𝑆𝑅 = 10 log (
2552
𝑀𝑆𝐸
)
𝑀𝑆𝐸 =
1
𝑁 × 𝑀
∑ ∑(𝐼𝑖,𝑗 − 𝐼𝑎𝑖,𝑗)
2
𝑀
𝑗
𝑁
𝑖
(5)
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where MSE is the mean square error, I and Ia are the original and the amplified frames respectively,
M and N are the frame dimensions.
b. MAXERR: is the absolute maximum squared deviation of the input video to the output video.
c. L2RAT: is the ratio of the squared base of the output video to the input video.
d. BRISQUE: The BRISQUE algorithm allows for the assessment of perceived quality using a model based
on natural images with self-ratings instead of a reference image.
We have achieved the tests by applying octave-bandwidth pyramid for PB-EVM, and IIR, FIR,
Butterworth, and Ideal band-pass as temporal filters. Several tests have been attained for the five videos as
shown in Figure 6.
a. For the first video (baby that is shown in Figure 6(a)), IIR is used as a temporal filter, the magnification
factor α with values {10, 30, 60, and 100} for LB-EVM and {60, 100, 200} for PB-EVM. While,
the values of boundary frequencies for the band-pass temporal filter are 0.4 Hz for the lowest frequency
and 4 Hz for the highest frequency for LB-EVM and {0.2-0.31 Hz} for PB-EVM. The value of sigma has
been chosen 5 for all the tests. Figure 7 shows sample frames (frames with orders 1, 20, 45, and 60) of the
source, magnified frames using conventional LB-EVM and magnified frames using the proposed
approach based LB-EVM at magnification factor α=20. Also, Figure 8 shows sample frames (frames with
orders 1, 20, 45, and 60) of the source, magnified frames using conventional PB-EVM and magnified
frames using the proposed approach based PB-EVM at magnification factor α=200. It is clear
the superiority of the proposed over the conventional ones in noise reduction. The proposed overcomes
the problem of linear noise magnification in conventional LB-EVM, also reduces noise significantly
compare to conventional PB_EVM for large magnification factor. Table 1 shows the experimental results
of both LB-EVM and PB-EVM methods for the proposed and conventional ones.
b. For the second video (camera that is shown in Figure 6(b)), Butterworth is used as a temporal
filter, α values are: {100, 150, 160} for LB-EVM and {100, 160, 250} for PB-EVM. The boundary of
temporal filter frequencies are {45-100 Hz} for LB-EVM and {36-62 Hz} for PB-EVM. The value of
sigma has been selected 5 for all the tests. Table 2 shows the experimental results of both LB-EVM and
PB-EVM methods for the proposed and conventional ones.
c. In the third video (guitar that is shown in Figure 6(c)), FIR is used as a temporal filter, α has values
{40, 50, 60} for LB-EVM and {40, 60, 120} for PB-EVM. The boundary of temporal filter frequencies
are {72-92 Hz} for the both LB-EVM and PB-EVM. The sigma has been selected 2 for all the tests.
Table 3 shows the experimental results of both LB-EVM and PB-EVM methods for the proposed and
conventional ones.
d. For the fourth video (face that is shown in Figure 6(d)), ideal band-pass is used as a temporal filter,
α with values {50, 60, 100, 150, and 200} using LB-EVM. The boundary frequencies for the band-pass
temporal filter are {0.83333-1 Hz}. This video is used in experimental tests in order to examine ability of
the proposed approach to detect and magnified the colour variation, also to detect and attenuate
movement variation. This is done based LB-EVM by increasing number of decomposition in spatial
domain to 7 levels. In our experiments, we see increasing number of decomposition lead to increase
the detection of colour variations, while decreasing the movement that we want to attenuate it because it
is not our interesting. Based our experimental tests, we conclude that for the videos with colour variations
linear-based method is better in order to reduce the unwanted motion in magnification process. Figure 9
shows sample frames of the source, magnified frames using conventional LB-EVM and magnified frames
using the proposed approach based LB-EVM at magnification factor α=200. From the figure, we can see
clearly the frame quality of the proposed approach better than the conventional one. Table 4 shows
the experimental results of for the proposed and conventional LB-EVM methods.
e. For the fifth video (eye that is shown in Figure 6(e)), FIR is used as a temporal filter, α with values
{65, 75, 85, 120, and 200} using PB-EVM method. The boundary of temporal filter frequencies is
{30–50 Hz}. The value of sigma has been selected 4 for all the tests. Table 5 shows the experimental
results of PB-EVM method for the proposed and conventional approaches.
In all the tests of the tables we see obviously superiority of the proposed approach in terms of
magnified video quality. Furthermore, in high magnification factors, the proposed approach resists the noise,
while the noise in conventional LB-EVM linearly increases and that’s lead to fail of the conventional one
with increasing α. Although high improvement in the magnified videos in terms of quality for the proposed
approach is verified, the processing time does not increase significantly, where the increment in processing
time less than 3% from the entire execution time using same software resources.
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(a) (b) (c) (d) (e)
Figure 6. The videos used in experimental results: (a) baby source video, (b) camera source video,
(c) guitar source video, (d) face source video, and (e) eye source video
1 20 45 60
(a)
1 20 45 60
(b)
1 20 45 60
(c)
Figure 7. Samples of the results using conventional and proposed LB-EVM
approaches at α=20: (a) the source frames; and amplified frames based on
(b) conventional and (c) proposed LB-EVM approach
1 20 45 60
(a)
1 20 45 60
(b)
1 20 45 60
(c)
Figure 8. Samples of the results using conventional and proposed PB-EVM
approaches at α=200: (a) the source frames; and amplified frames based on
(b) conventional and (c) proposed PB-EVM approach
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(a)
(b)
(c)
Figure 9. Samples of the results using conventional and proposed LB-EVM
approaches at α=200: (a) the source frames; and amplified frames based on
(b) conventional and (c) proposed LB-EVM approach
Table 1.The comparison results of the proposed and conventional,
LB-EVM and PB-EVM respectively, for the baby video
Input Video: Baby α = 10 α = 30 α = 60 α = 100 Input Video: Baby α = 60 α = 100 α = 200
Theconventional
LB-EVM[6]
Execution time 117.79 118.78 135.74 135.47
Theconventional
PB-EVM[7]
Execution time 228.14 231.73 231.33
PSNR 35.07 30.68 28.06 26.96 PSNR 29.40 27.25 25.08
MSE 20.23 55.60 101.64 130.94 MSE 74.66 122.48 201.87
MAXEER 65.67 134.83 175.41 200.40 MAXEER 133.48 145.17 155.99
L2RAT 0.9995 1.0033 1.0150 1.0411 L2RAT 0.9984 0.9962 0.9891
BRISQUE 46.79 50.23 51.97 52.46 BRISQUE 44.18 44.51 44.53
Theproposed
LB-EVM
Execution time 121.32 122.34 139.81 139.53
Theproposed
PB-EVM
Execution time 233.85 238.68 238.11
PSNR 41.91 36.50 33.23 31.09 PSNR 38.78 36.09 33.53
MSE 4.19 14.56 30.91 50.59 MSE 8.61 15.99 28.85
MAXEER 42.03 114.09 164.38 188.06 MAXEER 112.83 123.96 138.62
L2RAT 0.9989 0.9961 0.9948 0.9942 L2RAT 0.9991 0.9990 0.9986
BRISQUE 44.02 45.05 46.11 46.89 BRISQUE 41.18 42.62 43.18
Table 2.The comparison results of the proposed and conventional,
LB-EVM and PB-EVM respectively, for the camera video
Input Video: Camera α =100 α =150 α =160 Input Video: Camera α = 100 α = 160 α =250
Theconventional
LB-EVM[6]
Execution time 125.30 132.28 135.05
TheConventional
PB-EVM[7]
Execution time 262.95 264.85 266.44
PSNR 29.13 27.52 27.31 PSNR 32.54 30.33 28.37
MSE 79.44 115.10 120.80 MSE 36.23 60.28 94.64
MAXEER 52.14 81.63 87.22 MAXEER 180.13 192.12 298.26
L2RAT 1.0007 1.0067 1.0083 L2RAT 0.9935 0.9892 0.9852
BRISQUE 24.19 37.02 38.81 BRISQUE 30.99 31.82 32.93
Theproposed
LB-EVM
Execution time 129.05 136.25 139.10
Theproposed
PB-EVM
Execution time 270.84 272.79 274.43
PSNR 37.16 34.89 33.93 PSNR 37.26 35.80 33.24
MSE 12.50 21.09 26.31 MSE 12.22 17.10 30.84
MAXEER 24.63 40.33 43.61 MAXEER 124.10 152.11 184.86
L2RAT 0.9979 0.9991 0.9994 L2RAT 0.9811 0.9799 0.9771
BRISQUE 15.61 16.67 18.58 BRISQUE 28.40 28.89 29.01
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Table 3. The comparison among the proposed and conventional,
LB-EVM and PB-EVM respectively, for the guitar video
Input Video: Guitar α = 40 α = 50 α = 60 Input Video: Guitar α = 40 α = 60 α = 120
Theconventional
LB-EVM[6]
Execution time 27.29 28.17 29.58
Theconventional
PB-EVM[7]
Execution time 42.02 44.84 45.07
PSNR 34.20 33.32 32.48 PSNR 30.45 29.97 28.98
MSE 24.72 30.27 36.74 MSE 58.62 65.47 82.24
MAXEER 60.92 69.74 78.74 MAXEER 157.79 175.28 327.24
L2RAT 1.0015 1.0018 1.0021 L2RAT 0.9838 0.9824 0.9732
BRISQUE 22.27 23.80 23.92 BRISQUE 40.92 33.62 35.45
Theproposed
LB-EVM
Execution time 28.11 29.02 30.47
Theproposed
PB-EVM
Execution time 43.28 46.18 46.42
PSNR 38.90 38.16 37.82 PSNR 37.52 36.24 35.17
MSE 8.38 9.93 10.74 MSE 11.51 15.46 19.77
MAXEER 34.69 37.65 40.83 MAXEER 113.71 127.59 154.16
L2RAT 1.0004 1.0004 1.0004 L2RAT 0.9685 0.9680 0.9598
BRISQUE 20.59 20.61 20.67 BRISQUE 29.89 30.59 31.87
Table 4. The comparison results of the proposed and conventional using LB-EVM for the face video
Input Video: Face α = 50 α = 60 α = 100 α = 150 α = 200
The conventional
LB-EVM [6]
Execution time 42.42 43.28 44.58 45.06 46.61
PSNR 35.77 34.77 31.78 29.70 28.46
MSE 17.22 21.68 43.16 69.68 92.70
MAXEER 24.78 26.74 35.83 50.21 64.77
L2RAT 0.9993 0.9994 1.0006 1.0037 1.0086
BRISQUE 23.54 23.56 23.67 23.73 23.77
The proposed
LB-EVM
Execution time 43.69 44.58 45.92 46.41 48.00
PSNR 40.04 39.68 37.05 35.19 34.02
MSE 6.44 6.99 12.83 19.68 25.77
MAXEER 20.53 21.06 23.66 27.88 32.83
L2RAT 0.9986 0.9984 0.9977 0.9971 0.9970
BRISQUE 21.52 21.55 21.64 21.74 21.78
Table 5. The comparison results of the proposed and conventional using PB-EVM for the eye video
Input Video: Eye α = 65 α = 75 α = 85 α = 120 α = 200
The conventional
PB-EVM [7]
Execution Time 210.82 211.94 211.88 215.72 216.64
PSNR 32.85 32.53 32.25 31.49 30.12
MSE 33.73 36.31 38.73 46.14 63.25
MAXEER 201.38 206.73 209.30 217.59 223.58
L2RAT 0.9933 0.9925 0.9917 0.9892 0.9837
BRISQUE 35.67 37.45 39.08 42.53 46.13
The proposed
PB-EVM
Execution Time 217.14 218.29 218.24 222.19 222.71
PSNR 35.93 35.63 35.37 34.65 33.57
MSE 16.59 17.79 18.88 22.29 28.58
MAXEER 133.93 139.64 141.99 208.10 214.12
L2RAT 0.9906 0.9900 0.9897 0.9893 0.9854
BRISQUE 33.58 34.98 36.11 38.99 42.89
5. CONCLUSION
This paper has presented an efficient approach to reduce noise of magnified videos based EVM.
The proposed method employs wavelet transforms as a denoising tool and adds a pos-processing stage for
conventional LB-EVM and PB-EVM. The experimental results show the superiority of the proposed
approach over conventional linear and phase based Eulerian video magnification approaches in terms of
quality of the magnified videos. This allows amplifying the videos by larger amplification factor, so that new
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important hidden movements or colour variations can be detected. The processing time does not significantly
increase; the increment is only less than 3% of the overall execution time compare to conventional EVM.
Furthermore, the increasing levels of spatial decomposition in the proposed approach eliminate unwanted
movement in colour variation magnification, which causes a distortion in the magnified videos.
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BIOGRAPHIES OF AUTHORS
Haider Ismael Shahadi received his B.ESc degree in information engineering from
the University of Baghdad, Iraq in 2001, his master’s degree in Electronic and Communication
Engineering from the University of Baghdad-Iraq in 2004, and his Ph.D. in Electronic and
Communication Engineering from the Tenaga National University, Malaysia in 2014. Currently,
he is an assistant professor at the University of Kerbala, Iraq. His research interests include
digital signal and multimedia processing, data security, FPGA design and implementation and
embedded systems, IOT systems, and smart systems.
Zaid Jabbar Al-allaq received the Bachelor of Engineering in communication Techniques from
the Engineering Technical College, Al-Furat Al-Awsat Technical University, Najaf, Iraq,
in 2007, He is currently working toward the M.S. degree in the Department of communication
engineering, University of Al-Furat Al-Awsat Technical, Engineering Technical College, Najaf.
Hayder J. Albattat received a B.A.Sc. degree in Electrical Engineering Basra University, Iraq,
M.Scs. in Electrical Engineering (Electronics and communication –Image Processing) Electrical
engineering Department in Basra University, Iraq, and a Ph.D. degree in Electrical Engineering
(Electronics and communication) – University of Basra, Iraq. He is currently an Asst. Professor
in Electronic and Communication at Najaf Technical College / the Dpt. of Communication -
Al-Furat Al-Awsat Technical University.