In this paper, p-Laplace variational image inpainting model with symmetric Riesz fractional differential filter is proposed. Variational inpainting models are very useful to restore many smaller damaged regions of an image. Integer order variational image inpainting models (especially second and fourth order) work well to complete the unknown regions. However, in the process of inpainting with these models, any of the unindented visual effects such as staircasing, speckle noise, edge blurring, or loss in contrast are introduced. Recently, fractional derivative operators were applied by researchers to restore the damaged regions of the image. Experimentation with these operators for variational image inpainting led to the conclusion that second order symmetric Riesz fractional differential operator not only completes the damaged regions effectively, but also reducing unintended effects. In this article, The filling process of damaged regions is based on the fractional central curvature term. The proposed model is compared with integer order variational models and also GrunwaldLetnikov fractional derivative based variational inpainting in terms of peak signal to noise ratio, structural similarity and mutual information.
REMOVING OCCLUSION IN IMAGES USING SPARSE PROCESSING AND TEXTURE SYNTHESISIJCSEA Journal
We provide a solution to problem of occlusion in images by removing the occluding region and filling in the gap left behind. Inpainting algorithms fail in filling occlusions when the occluding region is large since there is loss of both structure and texture. We decompose the image into structure and texture images using a decomposition method based on sparseness of the image. The sparse reconstruction of the decomposed images result in an inpainted image with all the structures made intact. A texture synthesis is performed on the texture only image. Finally the structure and texture images are combined to get an image where the occlusion is filled. The performance of our algorithm in terms of visual effectiveness is compared with other algorithms used for inpainting.
Comparative analysis and implementation of structured edge active contour IJECEIAES
This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image. In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared. It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
Object recognition is the challenging problem in the real world application. Object recognition can be achieved through the shape matching. Shape matching is preceded by i) detecting the edges of the objects from the images. ii) Finding the correspondence between the shapes. iii) Measuring the dissimilarity between the shapes using the correspondence. iv) Classifying the object into classes by using this dissimilarity measures. In order to solve the correspondence problem, we attach a descriptor, the shape context, to each point. The shape context at a reference point captures the distribution of the remaining points relative to it, thus offering a globally discriminative characterization. Corresponding points on two similar shapes will have similar shape contexts. The one to one correspondence is achieved through the cost based bipartite graph matching. The cost matrix is reduced through Hungarian algorithm. The dissimilarity between the two shapes is computed using Canberra distance. The nearest neighbor classifier is used to classify the objects with the matching error. The results are obtained using the MATLAB for MINIST hand written digits.
Dictionary based Image Compression via Sparse Representation IJECEIAES
Nowadays image compression has become a necessity due to a large volume of images. For efficient use of storage space and data transmission, it becomes essential to compress the image. In this paper, we propose a dictionary based image compression framework via sparse representation, with the construction of a trained over-complete dictionary. The overcomplete dictionary is trained using the intra-prediction residuals obtained from different images and is applied for sparse representation. In this method, the current image block is first predicted from its spatially neighboring blocks, and then the prediction residuals are encoded via sparse representation. Sparse approximation algorithm and the trained overcomplete dictionary are applied for sparse representation of prediction residuals. The detail coefficients obtained from sparse representation are used for encoding. Experimental result shows that the proposed method yields both improved coding efficiency and image quality as compared to some state-of-the-art image compression methods.
Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Image Enhancement and Restoration by Image InpaintingIJERA Editor
Inpainting is the process of reconstructing lost or deteriorated part of images based on the background information. i. e .it fills the missing or damaged region in an image utilizing spatial information of its neighboring region. Inpainting algorithm have numerous applications. It is helpfully used for restoration of old films and object removal in digital photographs. The main goal of the algorithm is to modify the damaged region in an image in such a way that the inpainted region is undetectable to the ordinary observers who are not familiar with the original image. This proposed work presents image inpainting process for image enhancement and restoration by using structural, texture and exemplar techniques. This paper presents efficient algorithm that combines the advantages of these two approaches. We first note that exemplar-based texture synthesis contains the essential process required to replicate both texture and structure; the success of structure propagation, however, is highly dependent on the order in which the filling proceeds. We propose a best-first algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting. The actual color values are computed using exemplar-based synthesis. Computational efficiency is achieved by a blockbased sampling process.
REMOVING OCCLUSION IN IMAGES USING SPARSE PROCESSING AND TEXTURE SYNTHESISIJCSEA Journal
We provide a solution to problem of occlusion in images by removing the occluding region and filling in the gap left behind. Inpainting algorithms fail in filling occlusions when the occluding region is large since there is loss of both structure and texture. We decompose the image into structure and texture images using a decomposition method based on sparseness of the image. The sparse reconstruction of the decomposed images result in an inpainted image with all the structures made intact. A texture synthesis is performed on the texture only image. Finally the structure and texture images are combined to get an image where the occlusion is filled. The performance of our algorithm in terms of visual effectiveness is compared with other algorithms used for inpainting.
Comparative analysis and implementation of structured edge active contour IJECEIAES
This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image. In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared. It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
Object recognition is the challenging problem in the real world application. Object recognition can be achieved through the shape matching. Shape matching is preceded by i) detecting the edges of the objects from the images. ii) Finding the correspondence between the shapes. iii) Measuring the dissimilarity between the shapes using the correspondence. iv) Classifying the object into classes by using this dissimilarity measures. In order to solve the correspondence problem, we attach a descriptor, the shape context, to each point. The shape context at a reference point captures the distribution of the remaining points relative to it, thus offering a globally discriminative characterization. Corresponding points on two similar shapes will have similar shape contexts. The one to one correspondence is achieved through the cost based bipartite graph matching. The cost matrix is reduced through Hungarian algorithm. The dissimilarity between the two shapes is computed using Canberra distance. The nearest neighbor classifier is used to classify the objects with the matching error. The results are obtained using the MATLAB for MINIST hand written digits.
Dictionary based Image Compression via Sparse Representation IJECEIAES
Nowadays image compression has become a necessity due to a large volume of images. For efficient use of storage space and data transmission, it becomes essential to compress the image. In this paper, we propose a dictionary based image compression framework via sparse representation, with the construction of a trained over-complete dictionary. The overcomplete dictionary is trained using the intra-prediction residuals obtained from different images and is applied for sparse representation. In this method, the current image block is first predicted from its spatially neighboring blocks, and then the prediction residuals are encoded via sparse representation. Sparse approximation algorithm and the trained overcomplete dictionary are applied for sparse representation of prediction residuals. The detail coefficients obtained from sparse representation are used for encoding. Experimental result shows that the proposed method yields both improved coding efficiency and image quality as compared to some state-of-the-art image compression methods.
Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Image Enhancement and Restoration by Image InpaintingIJERA Editor
Inpainting is the process of reconstructing lost or deteriorated part of images based on the background information. i. e .it fills the missing or damaged region in an image utilizing spatial information of its neighboring region. Inpainting algorithm have numerous applications. It is helpfully used for restoration of old films and object removal in digital photographs. The main goal of the algorithm is to modify the damaged region in an image in such a way that the inpainted region is undetectable to the ordinary observers who are not familiar with the original image. This proposed work presents image inpainting process for image enhancement and restoration by using structural, texture and exemplar techniques. This paper presents efficient algorithm that combines the advantages of these two approaches. We first note that exemplar-based texture synthesis contains the essential process required to replicate both texture and structure; the success of structure propagation, however, is highly dependent on the order in which the filling proceeds. We propose a best-first algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting. The actual color values are computed using exemplar-based synthesis. Computational efficiency is achieved by a blockbased sampling process.
Image Matting via LLE/iLLE Manifold LearningITIIIndustries
Accurately extracting foreground objects is the problem of isolating the foreground in images and video, called image matting which has wide applications in digital photography. This problem is severely ill-posed in the sense that, at each pixel, one must estimate the foreground and background pixels and the so-called alpha value from only pixel information. The most recent work in natural image matting rely on local smoothness assumptions about foreground and background colours on which a cost function has been established. In this paper, we propose an extension to the class of affinity based matting techniques by incorporating local manifold structural
information to produce both a smoother matte based on the socalled improved Locally Linear Embedding. We illustrate our new algorithm using the standard benchmark images and very comparable results have been obtained.
Improving Performance of Texture Based Face Recognition Systems by Segmenting...IDES Editor
Textures play an important role in recognition of
images. This paper investigates the efficiency of performance
of three texture based feature extraction methods for face
recognition. The methods for comparative study are Grey Level
Co_occurence Matrix (GLCM), Local Binary Pattern (LBP)
and Elliptical Local Binary Template (ELBT). Experiments
were conducted on a facial expression database, Japanese
Female Facial Expression (JAFFE). With all facial expressions
LBP with 16 vicinity pixels is found to be a better face
recognition method among the tested methods. Experimental
results show that classification based on segmenting face
region improves recognition accuracy.
Hierarchical Approach for Total Variation Digital Image InpaintingIJCSEA Journal
The art of recovering an image from damage in an undetectable form is known as inpainting. The manual work of inpainting is most often a very time consum ing process. Due to digitalization of this technique, it is automatic and faster. In this paper, after the user selects the regions to be reconstructed, the algorithm automatically reconstruct the lost regions with the help of the information surrounding them. The existing methods perform very well when the region to be reconstructed is very small, but fails in proper reconstruction as the area increases. This paper describes a Hierarchical method by which the area to be inpainted is reduced in multiple levels and Total Variation(TV) method is used to inpaint in each level. This algorithm gives better performance when compared with other existing algorithms such as nearest neighbor interpolation, Inpainting through Blurring and Sobolev Inpainting.
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
We propose a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter-variations of the feature space dimensions. The obtained Riesz-covariance descriptors lie on a manifold governed by Riemannian geometry requiring specific geodesic metrics to locally approximate scalar products. The latter are used to construct a kernel for support vector machines (SVM). The effectiveness of the presented models is evaluated on a dataset of 92 patients with non-small cell lung carcinoma (NSCLC) and cancer recurrence information. Disease recurrence within a timeframe of 12 months could be predicted with an accuracy above 80, and highlighted the importance of covariance-based texture aggregation. At the end of the talk, computer tools will be presented to easily extract 3D radiomics quantitative features from PET-CT images.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Our life’s important part is Image. Without disturbing its overall structure of images, we can
remove the unwanted part of image with the help of image inpainting. There is simpler the inpainting of
the low resolution images than that of the high resolution images. In this system low resolution image
contained in different super resolution image inpainting methodologies and there are combined all these
methodologies to form the highly in painted image results. For this reason our system uses the super
resolution algorithm which is responsiblefor inpainting of singleimage.
Comparative Study and Analysis of Image Inpainting TechniquesIOSR Journals
Abstract: Image inpainting is a technique to fill missing region or reconstruct damage area from an image.It
removes an undesirable object from an image in visually plausible way.For filling the part of image, it use
information from the neighboring area. In this dissertation work, we present a Examplar based method for
filling in the missing information in an image, which takes structure synthesis and texture sysnthesis together.
In exemplar based approach it used local information from an image to patch propagation.We have also
implement Nonlocal Mean approach for exemplar based image inpainting.In Nonlocal mean approach it find
multiple samples of best exemplar patches for patch propagation and weight their contribution according to
their similarity to the neighborhood under evaluation. We have further extended this algorithm by considering
collaborative filtering method to synthesize and propagate with multiple samples of best exemplar patches. We
have to preformed experiment on many images and found that our algorithm successfully inpaint the target
region.We have tested the accuracy of our algorithm by finding parameter like PSNR and compared PSNR
value for all three different approaches.
Keywords: Texture Synthesis, Structure Synthesis, Patch Propagation ,imageinpainting ,nonlocal approach,
collabrative filtering.
EXTENDED WAVELET TRANSFORM BASED IMAGE INPAINTING ALGORITHM FOR NATURAL SCENE...cscpconf
This paper proposes an exemplar based image inpainting using extended wavelet transform. The
Image inpainting modifies an image with the available information outside the region to be
inpainted in an undetectable way. The extended wavelet transform is in two dimensions. The
Laplacian pyramid is first used to capture the point discontinuities, and then followed by a
directional filter bank to link point discontinuities into linear structures. The proposed model
effectively captures the edges and contours of natural scene images
Image Matting via LLE/iLLE Manifold LearningITIIIndustries
Accurately extracting foreground objects is the problem of isolating the foreground in images and video, called image matting which has wide applications in digital photography. This problem is severely ill-posed in the sense that, at each pixel, one must estimate the foreground and background pixels and the so-called alpha value from only pixel information. The most recent work in natural image matting rely on local smoothness assumptions about foreground and background colours on which a cost function has been established. In this paper, we propose an extension to the class of affinity based matting techniques by incorporating local manifold structural
information to produce both a smoother matte based on the socalled improved Locally Linear Embedding. We illustrate our new algorithm using the standard benchmark images and very comparable results have been obtained.
Improving Performance of Texture Based Face Recognition Systems by Segmenting...IDES Editor
Textures play an important role in recognition of
images. This paper investigates the efficiency of performance
of three texture based feature extraction methods for face
recognition. The methods for comparative study are Grey Level
Co_occurence Matrix (GLCM), Local Binary Pattern (LBP)
and Elliptical Local Binary Template (ELBT). Experiments
were conducted on a facial expression database, Japanese
Female Facial Expression (JAFFE). With all facial expressions
LBP with 16 vicinity pixels is found to be a better face
recognition method among the tested methods. Experimental
results show that classification based on segmenting face
region improves recognition accuracy.
Hierarchical Approach for Total Variation Digital Image InpaintingIJCSEA Journal
The art of recovering an image from damage in an undetectable form is known as inpainting. The manual work of inpainting is most often a very time consum ing process. Due to digitalization of this technique, it is automatic and faster. In this paper, after the user selects the regions to be reconstructed, the algorithm automatically reconstruct the lost regions with the help of the information surrounding them. The existing methods perform very well when the region to be reconstructed is very small, but fails in proper reconstruction as the area increases. This paper describes a Hierarchical method by which the area to be inpainted is reduced in multiple levels and Total Variation(TV) method is used to inpaint in each level. This algorithm gives better performance when compared with other existing algorithms such as nearest neighbor interpolation, Inpainting through Blurring and Sobolev Inpainting.
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
We propose a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter-variations of the feature space dimensions. The obtained Riesz-covariance descriptors lie on a manifold governed by Riemannian geometry requiring specific geodesic metrics to locally approximate scalar products. The latter are used to construct a kernel for support vector machines (SVM). The effectiveness of the presented models is evaluated on a dataset of 92 patients with non-small cell lung carcinoma (NSCLC) and cancer recurrence information. Disease recurrence within a timeframe of 12 months could be predicted with an accuracy above 80, and highlighted the importance of covariance-based texture aggregation. At the end of the talk, computer tools will be presented to easily extract 3D radiomics quantitative features from PET-CT images.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Our life’s important part is Image. Without disturbing its overall structure of images, we can
remove the unwanted part of image with the help of image inpainting. There is simpler the inpainting of
the low resolution images than that of the high resolution images. In this system low resolution image
contained in different super resolution image inpainting methodologies and there are combined all these
methodologies to form the highly in painted image results. For this reason our system uses the super
resolution algorithm which is responsiblefor inpainting of singleimage.
Comparative Study and Analysis of Image Inpainting TechniquesIOSR Journals
Abstract: Image inpainting is a technique to fill missing region or reconstruct damage area from an image.It
removes an undesirable object from an image in visually plausible way.For filling the part of image, it use
information from the neighboring area. In this dissertation work, we present a Examplar based method for
filling in the missing information in an image, which takes structure synthesis and texture sysnthesis together.
In exemplar based approach it used local information from an image to patch propagation.We have also
implement Nonlocal Mean approach for exemplar based image inpainting.In Nonlocal mean approach it find
multiple samples of best exemplar patches for patch propagation and weight their contribution according to
their similarity to the neighborhood under evaluation. We have further extended this algorithm by considering
collaborative filtering method to synthesize and propagate with multiple samples of best exemplar patches. We
have to preformed experiment on many images and found that our algorithm successfully inpaint the target
region.We have tested the accuracy of our algorithm by finding parameter like PSNR and compared PSNR
value for all three different approaches.
Keywords: Texture Synthesis, Structure Synthesis, Patch Propagation ,imageinpainting ,nonlocal approach,
collabrative filtering.
EXTENDED WAVELET TRANSFORM BASED IMAGE INPAINTING ALGORITHM FOR NATURAL SCENE...cscpconf
This paper proposes an exemplar based image inpainting using extended wavelet transform. The
Image inpainting modifies an image with the available information outside the region to be
inpainted in an undetectable way. The extended wavelet transform is in two dimensions. The
Laplacian pyramid is first used to capture the point discontinuities, and then followed by a
directional filter bank to link point discontinuities into linear structures. The proposed model
effectively captures the edges and contours of natural scene images
ANALYSIS OF INTEREST POINTS OF CURVELET COEFFICIENTS CONTRIBUTIONS OF MICROS...sipij
This paper focuses on improved edge model based on Curvelet coefficients analysis. Curvelet transform is
a powerful tool for multiresolution representation of object with anisotropic edge. Curvelet coefficients
contributions have been analyzed using Scale Invariant Feature Transform (SIFT), commonly used to study
local structure in images. The permutation of Curvelet coefficients from original image and edges image
obtained from gradient operator is used to improve original edges. Experimental results show that this
method brings out details on edges when the decomposition scale increases.
The usage of a fused image and compressed model in a VLSI implementation is demonstrated. In this study, distortion correction is also considered. In distortion correction models, least-squares estimate is utilized. The technique of picture fusion is widely employed in medical imaging. Many pictures are obtained from various sensors (or) multiple images are captured at different times by one sensor in the image fusion approach. CT scans give useful information on denser tissue with the least amount of distortion. The information obtained from a magnetic resonance imaging (MRI) of soft tissue with significant distortion is useful. The DWT-based image fusion approach employs discrete wavelet transforms, a novel multi-resolution analytic tool. Back mapping expansion polynomial is used to reduce computer complexity. Using 0.18um technology, the suggested VLSI design achieves 218MHz with 1480 logical components.
Dynamic texture based traffic vehicle monitoring systemeSAT Journals
Abstract Dynamic Textures are function of both space and time which exhibit spatio-temporal stationary property. They have spatially repetitive patterns which vary with time. In this paper, importance of phase spectrum in the signals is utilized and a novel method for vehicle monitoring is proposed with the help of Fourier analysis, synthesis and image processing. Methods like Doppler radar or GPS navigation are used commonly for tracking. The proposed image based approach has an added advantage that the clear image of the object (vehicle) can be used for future reference like proof of incidence, identification of owner and registration number. Keywords-Fourier Transform, dynamic texture, phase spectrum
A lossless color image compression using an improved reversible color transfo...eSAT Journals
Abstract In case of the conventional lossless color image compression methods, the pixels are interleaved from each color component, and they are predicted and finally encoded. In this paper, we propose a lossless color image compression method using hierarchical prediction of chrominance channel pixels and encoded with modified Huffman coding. An input image is chosen and the R, G and B color channel is transform into YCuCv color space using an improved reversible color transform. After that a conventional lossless image coder like CALIC is used to compress the luminance channel Y. The chrominance channel Cu and Cv are encoded with hierarchical decomposition and directional prediction. The effective context modeling for prediction residual is adopted finally. It is seen from the experimental result the proposed method improves the compression performance than the existing method. Keywords: Lossless color image compression, hierarchical prediction, reversible color transform, modified Huffman coding.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
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.
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.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
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.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Planning Of Procurement o different goods and services
p-Laplace Variational Image Inpainting Model Using Riesz Fractional Differential Filter
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 7, No. 2, April 2017, pp. 850 – 857
ISSN: 2088-8708 850
Institute of Advanced Engineering and Science
w w w . i a e s j o u r n a l . c o m
p-Laplace Variational Image Inpainting Model Using Riesz
Fractional Differential Filter
G Sridevi1
and S Srinivas Kumar2
1
Department of ECE, Aditya Engineering College, Kakinada, AP, India
2
Department of ECE, JNTUK, Kakinada, AP, India
Article Info
Article history:
Received May 25, 2016
Revised Mar 14, 2017
Accepted Mar 29, 2017
Keyword:
Fractional calculus
Image inpainting
Partial Differential Equations
Riesz fractional derivative
Variational models
ABSTRACT
In this paper, p-Laplace variational image inpainting model with symmetric Riesz fractional
differential filter is proposed. Variational inpainting models are very useful to restore many
smaller damaged regions of an image. Integer order variational image inpainting models
(especially second and fourth order) work well to complete the unknown regions. However,
in the process of inpainting with these models, any of the unindented visual effects such
as staircasing, speckle noise, edge blurring, or loss in contrast are introduced. Recently,
fractional derivative operators were applied by researchers to restore the damaged regions
of the image. Experimentation with these operators for variational image inpainting led to
the conclusion that second order symmetric Riesz fractional differential operator not only
completes the damaged regions effectively, but also reducing unintended effects. In this arti-
cle, The filling process of damaged regions is based on the fractional central curvature term.
The proposed model is compared with integer order variational models and also Grunwald-
Letnikov fractional derivative based variational inpainting in terms of peak signal to noise
ratio, structural similarity and mutual information.
Copyright c 2017 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
G Sridevi
Department of Electronics and Communication Engineering
Aditya Engineering College
Surampalem, Andhra Pradesh, India
sridevi gamini@yahoo.com
1. INTRODUCTION
Image inpainting, is an art of implementing untraceable modifications on images. It is used to restore the
damaged regions of an image based on the pixel information from the known regions. It is not only used to recover the
damaged parts but also used to discard the overlaid text and undesired objects. Inpainting is most useful in recovering
the old photographs and images in fine art museums. It can be used as a pre-processing step for other image processing
problems like image segmentation, pattern recognition and image registration. In this work, image inpainting model
for text removal and scratch removal are demonstrated.
The image inpainting techniques are mainly classified into three categories: textural inpainting, structural
inapinting and hybrid inpainting (combination of two approaches). Textural inpainting is mainly connected with the
texture synthesis. Many texture inpainting methods have been proposed since a famous texture synthesis algorithm
was developed by Efros and Leung [1]. Many other texture synthesis algorithms are proposed with the improvement
in speed and effectiveness of the Efros-Leung method.
Structure inpainting is the process of introducing smoothness priors to diffuse (propagate) local structured
information from source regions to unknown regions along the isophote direction. It uses partial differential equations
(PDE) and variational reconstructions methods. Marcelo et al. [2] introduced first PDE based digital image inpainting.
These models produce good results in restoring the non-textured or relatively smaller unknown regions. Navier-stokes
equations of fluid dynamics were used by the same authors, to inpaint the unknown regions by considering the image
intensity as a stream and isophote lines as flow of streamlines. However, these are slow iterative processes. In order
to minimize the computational time a fast marching technique is described in [3], which fills the unknown region in
Journal Homepage: http://iaesjournal.com/online/index.php/IJECE
Institute of Advanced Engineering and Science
w w w . i a e s j o u r n a l . c o m
, DOI: 10.11591/ijece.v7i2.pp850-857
2. IJECE ISSN: 2088-8708 851
single iteration using weighted means.
First variational approach to image completion was proposed by Masnou and Morel [4]. A famous variational
work was introduced by Chan and Shen [5] in 2001. Their method completes the missing regions by minimizing the
total variation (TV) norm. They retain the sharp edges for non-textured parts using curvature term in the corresponding
Euler-Lagrange equation. TV-norm converts smooth (flat) regions into piecewise constant levels (staircase effect).
Meanwhile, small details and textured regions are smoothed out. The TV inpainting model has been extended and
considerably improved in subsequent works, such as curvature driven diffusion [5], Euler’s elastica equation [6],
Gauss curvature driven diffusion [7], fractional curvature driven diffusion [8], fractional TV inpainting in spatial and
wavelet domain [9], and fractional order anisotropic diffusion [10].
Fractional differentiation[11], [12] finds an important role in the area of signal and image processing. Frac-
tional differentiation can be viewed as the generalization of integer differentiation. The definition of fractional dif-
ferentiation is not united. The commonly used definitions are proposed by the authors Gr¨unwald-Letnikov (G-L),
Riemann-Liouville (R-L), Caputo and Riesz. Many researchers have applied these definitions to many image process-
ing applications. Yi et al. [8] proposed G-L fractional derivative based curvature driven diffusion for the minimization
of metal artifacts in computerized X-ray images. Benoˆıt et al. [13] implemented fractional derivative for the detection
of edges. Yi-Fei et al. [14] constructed the fractional differential masks to enhance the texture elements in the images.
Yi et al. [15] proposed two new non-linear PDE image inpainting models using R-L fractional order derivative with
4-directional masks. Stanislas and Roberto [16] proposed fractional order diffusion for image reconstruction inspired
by the work of [17]. Qiang et al. [18] applied symmetric Riesz fractional derivative for enhancing the textured images.
Yi et al. [9] applied fractional order derivative defined by the second definition of Yi-Fei et al. [14] and filling process
is achieved by the fractional curvature term.
In this article, fractional derivative is combined with integer order variational inpainting model. The sec-
ond order symmetric Riesz fractional differential operator is considered in this work, because it possesses non-local
and anti-roational characteristics. The proposed model gives good visual effects and superior objective performance
metrics viz., PSNR, SSIM, and MI with respect to integer order variational image inpainting models.
This article is organized in five sections. In section 2, fractional order variational inpainting model is pre-
sented and fractional central curvature term is also represented. In section 3, construction of symmetric Riesz fractional
differential filter is presented. Simulation results are explained in section 4. Conclusions are given in section 5.
2. PROPOSED MODEL
Given an image, f € L2
pΩq, with Ω € R2
an inpainting or missing domain having boundary fΩ, and E an
surrounding domain nearby fΩ. The problem is to reconstruct the original image u from the observed image f.
A fractional order variational model is proposed in this article, which provides not only an effective image
inpainting, but also visible reduction of unintended effects. The proposed variational model mnimizes an energy cost
functional J, containing a mask that specify known and unknown regions of the image. Therefore, the completed and
enhanced image is determined as a result of the next minimization
Jαpupx, yqq 1
p
M¸
x1
M¸
y1
| α
upx, yq|p
λΩ
2
M¸
x1
M¸
y1
|upx, yq¡fpx, yq|2
(1)
where α is any real number and p € r1, 2s, the mask is based on the characteristic function of the inpainting region,
which is represented as
λΩ
5
λ, px, yq € Ω
0, otherwise
and the Neumann boundary condition fu{fn 0 is applied. Where n is an unit vector outward perpendicular to fΩ.
The first term of (1) is the fractional regularization term, which is used to inpaint the damaged parts based
on the non-local characteristics of the image. The second term of (1) is fidelity term, which is used to preserve the
important features like edges and λΩ is a scaling parameter in the inpainting region Ω, which is used to tune the weight
of two terms in the inpainting region only. According to the fractional calculus of variations, the Euler-Lagrange
equation is
p¡1qαdivα
¢ α
upx, yq
| αupx, yq|p2¡pq
λΩpupx, yq¡fpx, yqq 0 (2)
The computation of numerical algorithm is based on the gradient descent approach. and the following fractional vari-
atinal model is obtained.
p-Laplace Variational Image Inpainting Model Using Riesz Fractional Differential Filter (G Sridevi)
3. 852 ISSN: 2088-8708
fupx, yq
ft
p¡1qαcurvα
upx, yq λΩpupx, yq¡fpx, yqq (3)
The result of minimization (1), representing the restored image, will be determined by solving (3). The frac-
tional central curvature is introduced to increase the performance of image reconstruction. The discrete representation
of the fractional central curvature term curvα
upx, yq is represented as
curvα
upx, yq divα
¢ α
upx, yq
| αupx, yq|p2¡pq
α
x¡
¤
¥
α
x upx, yq
| α
x upx, yq|2 0.5 ¦| α
ycupx, yq|2
¨2¡p
2
α
y¡
¤
¥
α
y upx, yq
| α
y upx, yq|2 0.5 ¦| α
xcupx, yq|2
¨2¡p
2
(4)
where, is a small constant to stay away divide by zero. The proposed symmetric Riesz fractional differential filter
coefficients are used to diffuse the pixel information in the inpainting region based on fractional central curvature term.
The construction of the Riesz fractional differential coefficients will be explained in the next section.
3. CONSTRUCTION OF RIESZ FRACTIONAL DIFFERENTIAL FILTER
The second order symmetric fractional order derivative of upxqfor the infinite interval p¡V x Vqbased
on the Riesz definition is represented as a combination of the right and left sided R-L fractional derivatives
fα
f|x|α
upxq ¡cv
¢
fα
fp¡xqα
fα
fxα
upxq (5)
where cv
2cos
πα
2
¨¨¡1
with α $ 1, pm ¡1q α m 2 for m € N
fα
fp¡xqα
upxq 1
Γpm ¡αq
¢
¡ f
fx
m
V»
x
upmqpζq
pζ ¡xqα¡m 1
dζ (6)
fα
fxα
upxq 1
Γpm ¡αq
fm
fxm
x»
¡V
upζq
px ¡ζqα¡m 1
dζ (7)
The symmetric Riesz fractional order derivative is represented based on second order fractional centered difference
method [19] with step h,
fα
upxq
f|x|α
¡ 1
hα
V¸
k¡V
p¡1qk
Γpα 1q
Γ
α
2 ¡k 1
¨
Γ
α
2 k 1
¨upx ¡khq (8)
By noting Euler’s reflection formula for Gamma function, Γ
α
2
¨
Γ
1 ¡ α
2
¨
π
sinpπα
2 q and
Γ pαqΓ p1 ¡αq π
sinpπαq π
2sinpπα
2 qcospπα
2 q gives
Γ pαqΓ p1 ¡αq
Γ
α
2
¨
Γ
1 ¡ α
2
¨ 1
2cos
πα
2
¨ (9)
By substituting equ. (9) in equ.(8), one can has
fα
upxq
f|x|α
¡ 1
2cos
πα
2
¨
hα
V¸
k0
wα
k upk ¡xhq
0¸
k¡V
wα
k upk ¡xhq
'
(10)
where
wα
0 Γ
1 ¡ α
2
¨
αΓ
1 α
2
¨
Γp¡αq (11)
IJECE Vol. 7, No. 2, April 2017: 850 – 857
4. IJECE ISSN: 2088-8708 853
(a) (b) (c)
(d) (e) (f)
Figure 1. Fractional differential filters paqWα
x¡ pbqWα
x pcqWα
y¡ pdqWα
y peqWα
xc pfqWα
yc
wα
k p¡1qk 1
Γ
α
2
¨
Γ
1 ¡ α
2
¨
Γ
α
2 ¡k 1
¨
Γ
α
2 k 1
¨
Γp¡αq, k ¨1, ¨2, ... (12)
In the perspective of images, the smallest distance between the two pixels in x-direction and y-direction is
one. For a 2-D image, upx, yq at a pixel px1, y1q, in the positive x-direction N 1 pixels are considered. Therefore,
ukpx1, y1q upx1 ¡ kh, y1q, where h x1{N, 0 ¤ k ¤ N, and N is the number of divisions. Similar procedure
is considered in other directions, like positive y-direction, negative x-direction, negative y-direction. Consider h 1
and the anterior forward N 1 equivalent fractional order difference of the fractional partial differentiation in the
positive x-direction is
fα
upxq
f|x|α
! ¡ 1
2cos
πα
2
¨
hα
N¸
k0
wα
k upk ¡xhq, 0 α ¤ 2, α $ 1 (13)
For the central difference in x-direction of the image upx, yq at a pixel px1, y1q, N 1 pixels are considered in the
positive x-direction and N pixels are considered in the negative x-direction. Therefore, ukpx1, y1q upx1 ¡kh, y1q¡
upx1 kh, y1q. Similar procedure is considered for central y-direction. So, the anterior 2N 1 equivalent fractional
order centeral difference of the fractional partial differentiation in the central x-direction is
fα
upxq
f|x|α
! ¡ 1
2cos
πα
2
¨
hα
N¸
k¡N
wα
k upk ¡xhq, 0 α ¤ 2, α $ 1 (14)
The fractional differential filters along symmetric directions, the positive x-axis pWα
x q, negative x-axis
pWα
x¡q, positive y-axis pWα
y q, negative y-axis pWα
y¡q, central x-axis pWα
xcq, central y-axis pWα
ycq are constructed
p-Laplace Variational Image Inpainting Model Using Riesz Fractional Differential Filter (G Sridevi)
5. 854 ISSN: 2088-8708
(a) (b) (c) (d) (e)
(f) (g) (h) (i) (j)
Figure 2. Comparison of variational inpainting models for text removal (a) Ground truth image, (f) Image with overlaid
text (PSNR = 17.75 dB), (b) Inpainted image using TV model [20] (PSNR = 30.45 dB), (c) Inpainted image using
fourth order PDE model [21] (PSNR=31.6 dB), (d) Inpainted image using Yi et al. model [9] (PSNR = 31.6 dB), (e)
Inpainted image using proposed model (PSNR = 32.8 dB), (g) Enlargement of parrot’s face of (b), (h) Enlargement of
parrot’s face of (c), (i) Enlargement of parrot’s face of (d), (j) Enlargement of parrot’s face of (e)
and shown in Figure 1. These fractional differential filters possess non-local and anti-rotational properties. In Figure
1, Cα
u0
is the filter coefficient corresponding with the interested pixel. The size of the filter is 2N 1, where N is any
positive integer and, one implements p2N 1q ¢ p2N 1q fractional differential filter. Airspace filtering technique
is performed on the symmetric directions with p2N 1q ¢ p2N 1q fractional differential filter. The usage of the
airspace filter is to move the window pixel by pixel and these are computed using
α
l upx, yq
N¸
i¡N
N¸
j¡N
Wα
l pi, jqupx i, y jq (15)
where l x , x¡, y , y¡, xc, yc
The fractional differential filter coefficients are
Cα
u0
1
2cos
πα
2
¨
pα ¡1qΓ
1 ¡ α
2
¨
Γ
1 α
2
¨
Γp2 ¡αq (16)
Cα
uk
1
2cos
πα
2
¨
p¡1qk
αpα ¡1qΓ
α
2
¨
Γ
1 ¡ α
2
¨
Γ
α
2 ¡k 1
¨
Γ
α
2 k 1
¨
Γp2 ¡αq, k ¨1, ¨2, ... (17)
4. RESULTS AND DISCUSSION
The proposed technique described here has been tested on large collections of images affected by missing
regions. The USC-SIPI database is used in our experiments. The proposed technique provides an effective restoration
of the degraded image, completing successfully the missing zones. It also preserves the image details, like edges, and
reduces the unintended effects, such as image blurring, staircasing and speckle effects. The optimal image reconstruc-
tion results are achieved by the proper selection of fractional order. This value is detected by trial and error, through
emprical observation. In this work, when α 1.4 the proposed model produces optimal reconstruction result.
The performance of this fractional order vartional model has been quantified by using well-known measures,
such as peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) [22], and Mutual Information (MI)[23].
This approach outperforms numereous state of the art inpainting methods. This fractional order variational image
IJECE Vol. 7, No. 2, April 2017: 850 – 857
6. IJECE ISSN: 2088-8708 855
inpainting technique is able to restore multiple missing regions. For this reason, it can be successfully used for some
important tasks, such as removing the superimposed text, removing the scratches, or removing the watermarks from
the digital images.
A text removing example using proposed technique described in Figure 2, wheresome method comparison
results are displayed. The images of that figure depict the inpainting results achieved by various inpainting techniques
on the parrots color image collected from LIVE image database and cropped to [256 X 256] . The text is superimposed
on the image and the inpainting techiniques are are applied. These inpainting techniques are carried out in YCbCr
color space. The text is almost removed by all the models. However, one can observe that, the texture part near the
parrot’s eye is not restored well by state of the art methods, such as TV inpainting b), fourth order PDE model c), and
Yi et al. model d) [9]. These models do not preserve edges and produce loss in contrast. The zoomed version of these
techniques are shown in Figure 2(g)-(j). The inpainting regions after applying the proposed model are filled effectively
than the other three models. Inpainting models for text removal with the same damaged mask are applied on different
images and registerd in Table 1. As one could observe in that table, the performance measures of proposed inpainting
technique achieve the highest values. One more observation is that, the proposed model works well even if the image
having partially textured regions, but the other three models are not. The logic is that, the total variation model is
second order PDE, Yi et al. model (α=1.8) is closed to fourth order PDE, where as the proposed model (α=1.4) is
closed to third order PDE.
(a) (b) (c) (d) (e)
(f) (g) (h) (i) (j)
Figure 3. Inpainting of artificial lines on pepper’s image (a) Ground truth image, (f) Damaged image (PSNR=16.60dB)
(b) Inpainted image using TV model [20] (PSNR = 33.97 dB, SSIM = 0.9001, MI = 3.6850), (c) Inpainted image using
fourth order PDE model [21] (PSNR = 33.89 dB, SSIM = 0.9312, MI = 3.8402), (d) Inpainted image using Yi et al.
model [9] (PSNR = 35.9 dB, SSIM = 0.9497, MI = 4.3149) (e) Inpainted image using proposed model (PSNR = 36.16
dB, SSIM = 0.9712, MI = 5.4789), (g) Residual image of (b), (h) Residual image of (c), (i) Residual image of (d), (j)
Residual image of (e)
Table 1. Comparison of inpainting models for text removal on different images
Image I/P
PSNR
TV [20] Fourth order PDE [21] Yi et al. [9] Proposed model
PSNR SSIM MI PSNR SSIM MI PSNR SSIM MI PSNR SSIM MI
Cameraman 16.16 30.38 0.9374 3.74 30.58 0.9379 3.75 31.05 0.9396 3.79 32.94 0.9473 5.23
Elaine 18.69 38.16 0.9420 4.89 38.56 0.9478 4.92 38.72 0.9587 4.94 39.60 0.9694 5.95
Lena 19.60 34.21 0.9288 4.51 34.32 0.9327 4.57 34.52 0.9369 4.64 35.02 0.9532 5.75
Mandrill 19.53 31.18 0.8275 3.03 31.20 0.8349 3.04 31.23 0.8455 3.06 33.53 0.9516 4.80
The proposed model is also applied to remove the unwanted scratches from the image. The simulation results
on pepper’s image are shown in Figure 3. This inpainting technique outperforms the TV inpainting, fourth order PDE
model, Yi et al. model. The experiment shows the loss of contrast after applying the inpainting techniques. In order
p-Laplace Variational Image Inpainting Model Using Riesz Fractional Differential Filter (G Sridevi)
7. 856 ISSN: 2088-8708
Table 2. Comparison of inpainting models for scratch removal on different images
Image I/P
PSNR
TV [20] Fourth order PDE [21] Yi et al. [9] Proposed model
PSNR SSIM MI PSNR SSIM MI PSNR SSIM MI PSNR SSIM MI
Cameraman 17.47 26.68 0.8020 3.05 26.55 0.8532 3.22 27.64 0.9290 3.82 29.20 0.9234 5.28
Man 18.24 32.21 0.9050 3.48 31.76 0.9145 3.42 32.10 0.9277 3.64 33.52 0.9493 5.11
Lena 16.64 31.84 0.8762 3.94 32.42 0.9124 3.60 32.68 0.9381 3.96 33.26 0.9590 5.15
House 16.97 34.74 0.8522 3.08 34.94 0.8865 3.22 34.87 0.9043 3.42 35.91 0.9211 4.93
to understand the loss of contrast, the residual images pf ¡u 100q are shown in Figure 3(g)-(j). Figure 3(g), shows
the result of total variation inpainting. It produces loss in contrast and edges are also blurred. Fourth order PDE model
fills the damaged regions effectively than TV model. However, edges are smoothed. Yi et al. model preserves the
contrast to some extent only because the fractional curvature term is applied, which is based on forward and backward
fractional differences. The proposed model uses fractional central differences. Hence, there is no loss in contrast
and edges are also not blurred by the proposed model. When the fractional order is 1.4, the proposed model gives
higher results than other models in terms of PSNR, SSIM, and MI also in visual quality. The inpainting techniques
on different images with the same mask are applied and the simulation results are registered in Table 2. One could
observe that, the performance measures of proposed inpainting technique achieve the highest values.
5. CONCLUSIONS
In this article, symmetric Riesz fractional differential filter is applied to p-Laplace variational image in-
painting. Fractional order variational inpainting models restored superior to integer order variational models. The
symmetric Riesz filter possesses non-local property, anti-rotational property, and inpainting region is filled based on
the fractional central curvature term. It uses forward, backward, and fractional central differences. Therefore, this
model provides the effective image inpainting and overcomes the unintended visual effects. The simulation results
display that the performance of the proposed model is exceeding integer order variational models and Yi et al. model
[9].
REFERENCES
[1] A. A. Efros and T. K. Leung, “Texture synthesis by non-parametric sampling,” in The Proceedings of the Seventh
IEEE International Conference on Computer Vision, vol. 2. IEEE, 1999, pp. 1033–1038.
[2] B. Marcelo, S. Guillermo, C. Vincent, and B. Coloma, “Image inpainting,” in Proceedings of the 27th annual
conference on Computer graphics and interactive techniques. ACM Press/Addison-Wesley Publishing Co.,
2000, pp. 417–424.
[3] T. Alexandru, “An image inpainting technique based on the fast marching method,” Journal of graphics tools,
vol. 9, no. 1, pp. 23–34, 2004.
[4] S. Masnou and J.-M. Morel, “Level lines based disocclusion,” in International Conference on Image Processing,
1998. IEEE, 1998, pp. 259–263.
[5] C. F. Tony and S. Jianhong, “Nontexture inpainting by curvature-driven diffusions,” Journal of Visual Commu-
nication and Image Representation, vol. 12, no. 4, pp. 436–449, 2001.
[6] C. F. Tony, K. H. Sung, and S. Jianhong, “Euler’s elastica and curvature-based inpainting,” SIAM Journal on
Applied Mathematics, pp. 564–592, 2002.
[7] P. Jidesh and S. George, “Gauss curvature-driven image inpainting for image reconstruction,” Journal of the
Chinese Institute of Engineers, vol. 37, no. 1, pp. 122–133, 2014.
[8] Z. Yi, P. Yi-Fei, H. Jin-Rong, L. Yan, C. Qing-Li, and Z. Ji-Liu, “Efficient ct metal artifact reduction based on
fractional-order curvature diffusion,” Computational and mathematical methods in medicine, vol. 2011, 2011.
[9] Z. Yi, P. Yi-Fei, J. Hu, and Z. Ji Liu, “A class of fractional-order variational image inpainting models,” Applied
Mathematics and Information Sciences, vol. 6, no. 2, pp. 299–306, 2012.
[10] G. Sridevi and S. S. Kumar, “Image inpainting models using fractional order anisotropic diffusion,” International
Journal of Image, Graphics and Signal Processing (IJIGSP), vol. 8, no. 10, pp. 1–10, 2016.
[11] K. B. Oldham and J. Spanier, The fractional calculus. Elsevier, 1974.
[12] J. Abdelhamid, K. Jelassi, and J.-C. Trigeassou, “A comparative study of identification techniques for fractional
models,” International Journal of Electrical and Computer Engineering, vol. 3, no. 2, pp. 186–196, 2013.
[13] M. Benoˆıt, M. Pierre, O. Alain, and C. Ceyral, “Fractional differentiation for edge detection,” Signal Processing,
vol. 83, no. 11, pp. 2421–2432, 2003.
IJECE Vol. 7, No. 2, April 2017: 850 – 857
8. IJECE ISSN: 2088-8708 857
[14] P. Yi-Fei, Z. Ji-Liu, and Y. Xiao, “Fractional differential mask: A fractional differential-based approach for
multiscale texture enhancement,” IEEE Transactions on Image Processing, vol. 19, no. 2, pp. 491–511, 2010.
[15] Z. Yi, P. Yi Fei, and Z. J. Liu, “Two new nonlinear pde image inpainting models,” in Computer Science for
Environmental Engineering and EcoInformatics. Springer, 2011, pp. 341–347.
[16] L. Stanislas and M. Roberto, “Fractional-order diffusion for image reconstruction,” in IEEE International Con-
ference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2012, pp. 1057–1060.
[17] B. Jian and F. C. Xiang, “Fractional-order anisotropic diffusion for image denoising,” IEEE Transactions on
Image Processing, vol. 16, no. 10, pp. 2492–2502, 2007.
[18] Y. Qiang, F. Liu, I. Turner, K. Burrage, and V. Vegh, “The use of a riesz fractional differential-based approach
for texture enhancement in image processing,” ANZIAM Journal, vol. 54, pp. 590–607, 2013.
[19] O. Manuel Duarte, “Riesz potential operators and inverses via fractional centred derivatives,” International Jour-
nal of Mathematics and Mathematical Sciences, vol. 2006, 2006.
[20] S. Jianhong and C. F. Tony, “Mathematical models for local nontexture inpaintings,” SIAM Journal on Applied
Mathematics, vol. 62, no. 3, pp. 1019–1043, 2002.
[21] Y.-L. You and M. Kaveh, “Fourth-order partial differential equations for noise removal,” IEEE Transactions on
Image Processing, vol. 9, no. 10, pp. 1723–1730, 2000.
[22] W. Zhou, B. C. Alan, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to
structural similarity,” IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, 2004.
[23] Q. Guihong, Z. Dali, and Y. Pingfan, “Information measure for performance of image fusion,” Electronics letters,
vol. 38, no. 7, pp. 313–315, 2002.
BIOGRAPHIES OF AUTHORS
G Sridevi received B.Tech degree in Electronics and Communication Engineering from Nagarjuna
University, Andhra Pradesh, India and Masters degree from Jawaharlal Nehru Technological Uni-
versity, Kakinada, Andhra Pradesh, India in 2000 and 2009 respectively. She is currently pursuing
her Ph.D in Jawaharlal Nehru Technological University, Kakinada. Her areas of interest are Digital
image processing and Digital signal processing. She has more than 14 years of teaching expe-
rience. She is presently working as an Associate professor in the department of Electronics and
Communication Engineering in Aditya Engineering College, Surampalem, Andhra Pradesh. She is
the member of Institution of Electronics and Telecommunication Engineers.
S Srinivas Kumar is working as a Professor in the department of Electronics and Communication
Engineering and Director (Research and Development), JNTU College of Engineering, Kakinada,
India. He received his M.Tech. from Jawaharlal Nehru Technological University, Hyderabad, India.
He received his Ph.D. from E ECE Department, IIT Kharagpur. He has twenty eight years of
experience in teaching and research. He has published more than 50 research papers in National
and International journals. Five Research scholars have completed their Ph. D and presently 11
research scholars are working under his supervision in the areas of Image processing and Pattern
recognition. His research interests are Digital image processing, Computer vision, and application
of Artificial neural networks and Fuzzy logic to engineering problems.
p-Laplace Variational Image Inpainting Model Using Riesz Fractional Differential Filter (G Sridevi)