This document provides a summary of feature extraction techniques in both the spatial and transformed domains. In the spatial domain, traditional methods like Canny, Sobel, and Harris detectors are discussed. The paper then focuses on the Scale Invariant Feature Transform (SIFT) technique developed by David Lowe, which extracts local features that are invariant to scale, rotation, and illumination changes. Several variants of SIFT are also examined, including PCA-SIFT, ASIFT, and A2SIFT, which improve robustness, distinctiveness, and performance. In the transformed domain section, the document explores techniques that use Fourier and wavelet transforms for feature extraction.
Shot Boundary Detection using Radon Projection MethodIDES Editor
The detection of shot boundaries provides a base for
nearly all video abstraction and high-level video segmentation
approaches. Therefore solving the problem of shot boundary
detection is one of the major prerequisites for revealing
higher level video content structure. As a crucial step in video
indexing and retrieval, accurate shot boundary detection plays
an important role to organize and summarize video content
into meaningful shots for further scene analysis. Many
algorithms have been proposed for detecting video shot
boundaries and classifying shots and shot transition types. In
this paper we propose a novel technique for shot boundary
detection using radon transform. We first removed the effect
of illumination using DCT and DWT. Then shot boundary is
detected using radon transform. Radon transform is based on
projection of image intensity along a radial line oriented at a
specific angle. Projection of image intensity for current frame
is different than that of projection of the previous frame, where
shot boundary is detected. In order to verify the performance
of algorithm, experiments have been carried out with news,
documentary and movie. Experimental result demonstrates
efficiency of proposed shot boundary detection technique.
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.
A Novel Approach for Ship Recognition using Shape and Texture ijait
Maritime security includes reliable identification of ship entering and leaving a nation’s territorial waters. Sea target detection from remote sensing imagery is very important, with a wide array of applications in areas such as fishery management, vessel traffic services, and naval warfare. Automated systems that could identify a ship could complement existing electronic signal identification methods. A new classification approach using shape and texture is introduced for Ship detection. Texture information can improve classification performance. This approach uses both shape and texture features. Feature extraction is done by Hu’s moment invariants with several classification algorithms. This paper presents an overview of
automatic ship recognition methods with a view towards embedded implementation on optical smart cameras. Therefore this approach may attain a good classification rate.
AN OPTIMAL SOLUTION FOR IMAGE EDGE DETECTION PROBLEM USING SIMPLIFIED GABOR W...IJCSEIT Journal
Edge detection plays a vital role in computer vision and image processing. Edge of the image is one of the
most significant features which are mainly used for image analyzing process. An efficient algorithm for
extracting the edge features of images using simplified version of Gabor Wavelet is proposed in this paper.
Conventional Gabor Wavelet is widely used for edge detection applications. Due do the high computational
complexity of conventional Gabor Wavelet, this may not be used for real time application. Simplified Gabor
wavelet based approach is highly effective at detecting both the location and orientation of edges. The
results proved that the performance of proposed Simplified version of Gabor wavelet is superior to
conventional Gabor Wavelet, other edge detection algorithm and other wavelet based approach. The
performance of the proposed method is proved with the help of FOM, PSNR and Average run time.
Touchless Palmprint Verification using Shock Filter, SIFT, I-RANSAC, and LPD iosrjce
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.
Orientation Effectiveness in the Objects Detected Areas Using Different Types...IJCSES Journal
This paper presents a study for the orientation effectiveness on the detected areas for many sampled objects when many type of the edges detection are applied. The Canny, Laplace, Prewitt and Sobel are applied for three objects (pencils’ sharpeners with different colors). The MBR (Minimal Bounding Rectangular) are used to calculate the area in pixels, centroid and the orientation. The MR (Misclassification Ratio) is used to find the different between the edges detection techniques. The Canny edges detection technique gives the best result for the three used object using all orientations.
CLASSIFICATION AND COMPARISON OF LICENSE PLATES LOCALIZATION ALGORITHMSsipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
Shot Boundary Detection using Radon Projection MethodIDES Editor
The detection of shot boundaries provides a base for
nearly all video abstraction and high-level video segmentation
approaches. Therefore solving the problem of shot boundary
detection is one of the major prerequisites for revealing
higher level video content structure. As a crucial step in video
indexing and retrieval, accurate shot boundary detection plays
an important role to organize and summarize video content
into meaningful shots for further scene analysis. Many
algorithms have been proposed for detecting video shot
boundaries and classifying shots and shot transition types. In
this paper we propose a novel technique for shot boundary
detection using radon transform. We first removed the effect
of illumination using DCT and DWT. Then shot boundary is
detected using radon transform. Radon transform is based on
projection of image intensity along a radial line oriented at a
specific angle. Projection of image intensity for current frame
is different than that of projection of the previous frame, where
shot boundary is detected. In order to verify the performance
of algorithm, experiments have been carried out with news,
documentary and movie. Experimental result demonstrates
efficiency of proposed shot boundary detection technique.
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.
A Novel Approach for Ship Recognition using Shape and Texture ijait
Maritime security includes reliable identification of ship entering and leaving a nation’s territorial waters. Sea target detection from remote sensing imagery is very important, with a wide array of applications in areas such as fishery management, vessel traffic services, and naval warfare. Automated systems that could identify a ship could complement existing electronic signal identification methods. A new classification approach using shape and texture is introduced for Ship detection. Texture information can improve classification performance. This approach uses both shape and texture features. Feature extraction is done by Hu’s moment invariants with several classification algorithms. This paper presents an overview of
automatic ship recognition methods with a view towards embedded implementation on optical smart cameras. Therefore this approach may attain a good classification rate.
AN OPTIMAL SOLUTION FOR IMAGE EDGE DETECTION PROBLEM USING SIMPLIFIED GABOR W...IJCSEIT Journal
Edge detection plays a vital role in computer vision and image processing. Edge of the image is one of the
most significant features which are mainly used for image analyzing process. An efficient algorithm for
extracting the edge features of images using simplified version of Gabor Wavelet is proposed in this paper.
Conventional Gabor Wavelet is widely used for edge detection applications. Due do the high computational
complexity of conventional Gabor Wavelet, this may not be used for real time application. Simplified Gabor
wavelet based approach is highly effective at detecting both the location and orientation of edges. The
results proved that the performance of proposed Simplified version of Gabor wavelet is superior to
conventional Gabor Wavelet, other edge detection algorithm and other wavelet based approach. The
performance of the proposed method is proved with the help of FOM, PSNR and Average run time.
Touchless Palmprint Verification using Shock Filter, SIFT, I-RANSAC, and LPD iosrjce
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.
Orientation Effectiveness in the Objects Detected Areas Using Different Types...IJCSES Journal
This paper presents a study for the orientation effectiveness on the detected areas for many sampled objects when many type of the edges detection are applied. The Canny, Laplace, Prewitt and Sobel are applied for three objects (pencils’ sharpeners with different colors). The MBR (Minimal Bounding Rectangular) are used to calculate the area in pixels, centroid and the orientation. The MR (Misclassification Ratio) is used to find the different between the edges detection techniques. The Canny edges detection technique gives the best result for the three used object using all orientations.
CLASSIFICATION AND COMPARISON OF LICENSE PLATES LOCALIZATION ALGORITHMSsipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
CLASSIFICATION AND COMPARISON OF LICENSE PLATES LOCALIZATION ALGORITHMSsipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
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.
Video Shot Boundary Detection Using The Scale Invariant Feature Transform and...IJECEIAES
Segmentation of the video sequence by detecting shot changes is essential for video analysis, indexing and retrieval. In this context, a shot boundary detection algorithm is proposed in this paper based on the scale invariant feature transform (SIFT). The first step of our method consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. The overview step provides the locations of boundaries. Secondly, a moving average calculation is performed to determine the type of transition. The proposed method can be used for detecting gradual transitions and abrupt changes without requiring any training of the video content in advance. Experiments have been conducted on a multi type video database and show that this algorithm achieves well performances.
Enhanced Optimization of Edge Detection for High Resolution Images Using Veri...ijcisjournal
dge Detection plays a crucial role in Image Processing and Segmentation where a set of algorithms aims
to identify various portions of a digital image at which a sharpened image is observed in the output or
more formally has discontinuities. The contour of Edge Detection also helps in Object Detection and
Recognition. Image edges can be detected by using two attributes such as Gradient and Laplacian. In our
Paper, we proposed a system which utilizes Canny and Sobel Operators for Edge Detection which is a
Gradient First order derivative function for edge detection by using Verilog Hardware Description
Language and in turn compared with the results of the previous paper in Matlab. The process of edge
detection in Verilog significantly reduces the processing time and filters out unneeded information, while
preserving the important structural properties of an image. This edge detection can be used to detect
vehicles in Traffic Jam, Medical imaging system for analysing MRI, x-rays by using Xilinx ISE Design
Suite 14.2.
Geometric wavelet transform for optical flow estimation algorithmijcga
This paper described an algorithm for computing the optical flow (OF) vector of a moving objet in a video sequence based on geometric wavelet transform (GWT). This method tries to calculate the motion between two successive frames by using a GWT. It consists to project the OF vectors on a basis of geometric wavelet. Using GWT for OF estimation has been attracting much attention. This approach takes advantage of the geometric wavelet filter property and requires only two frames. This algorithm is fast and able to estimate the OF with a low-complexity. The technique is suitable for video compression, and can be used for stereo vision and image registration.
ROLE OF HYBRID LEVEL SET IN FETAL CONTOUR EXTRACTIONsipij
Image processing technologies may be employed for quicker and accurate diagnosis in analysis and
feature extraction of medical images. Here, existing level set algorithm is modified and it is employed for
extracting contour of fetus in an image. In traditional approach, fetal parameters are extracted manually
from ultrasound images. An automatic technique is highly desirable to obtain fetal biometric measurements
due to some problems in traditional approach such as lack of consistency and accuracy. The proposed
approach utilizes global & local region information for fetal contour extraction from ultrasonic images.
The main goal of this research is to develop a new methodology to aid the analysis and feature extraction.
Cracks on the concrete surface are one of the earliest symptoms of degradation of the structure which isfundamental for the upkeep as properly the non-stop publicity will lead to the severe injury to the environment.Manual inspection is the acclaimed approach for the crack inspection. In the guide inspection, the diagram of thecrack is organized manually, and the conditions of the irregularities are noted. Since the guide strategy absolutelyrelies upon on the specialist’s expertise and experience, it lacks objectivity in the quantitative analysis. So,automated image-based crack detection is proposed as a replacement. The proposed gadget comprises pictureprocessing and facts acquisition methodologies for crack detection and evaluation of surface degradation. Theacquired outcomes exhibit that the deployment of image processing in an nice way is a key step towards theinspection of giant infrastructures
Enhanced Face Detection Based on Haar-Like and MB-LBP FeaturesDr. Amarjeet Singh
The effective real-time face detection framework
proposed by Viola and Jones gained much popularity due its
computational efficiency and its simplicity. A notable
variant replaces the original Haar-like features with MBLBP (Multi-Block Local Binary Pattern) which are defined
by the local binary pattern operator, both detector types are
integrated into the OpenCV library. However, each
descriptor and its evaluation method has its own set of
strengths and setbacks. In this paper, an enhanced two-layer
face detector composed of both Haar-like and MB-LBP
features is presented. Haar-like features are employed as a
coarse filter but with a new evaluation involving dual
threshold. The already established MB-LBPs are arranged
as the fine filter of the detector. The Gentle AdaBoost
learning algorithm is deployed for the training of the
proposed detector to reach the classification and
performance potential. Experiments show that in the early
stages of classification, Haar features with dual threshold
are more discriminative than MB-LBP and original Haarlike features with respect to number of features required
and computation. Benchmarking the proposed detector
demonstrate overall 12% higher detection rate at 17% false
alarm over using MB-LBP features singly while performing
with ×3 speedup.
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.
This paper presents crack detection in concrete structure based on fuzzy logic. Safety inspection of concrete structures is very important since it is closely related with the structural health and reliability. Automated structural health monitoring system becomes necessity in recent years that encourages various researches to be going on in this area. Cheap availability of digital cameras makes research work in this field easier. This paper presents digital image processing and fuzzy logic based efficient crack detection technique in concrete structure. Here features from digital image of concrete structure are extracted by using morphological image processing technique and then extracted features are fed to fuzzy logic to accurately identify the crack.
Application of feature point matching to video stabilizationNikhil Prathapani
One of the significant application of computer vision is Stabilizing a video that was captured from a jittery or moving platform. One way to stabilize a video is to track a prominent feature in the image and utilize it as an anchor point to cancel out all perturbations relative to it. This technique, however, must be bootstrapped with knowledge of where such a salient feature remains in the first video frame. The paper presents method of video stabilization that works without any such erstwhile knowledge. The method is built on the basis of Random Sampling and Consensus (RANSAC) and adding few additions to the existing methodologies. It instead automatically investigates for the "background plane" in a video sequence, and utilizes its observed distortion to precise for camera motion. All the simulations have been performed using MATLAB tool.
CLASSIFICATION AND COMPARISON OF LICENSE PLATES LOCALIZATION ALGORITHMSsipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
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.
Video Shot Boundary Detection Using The Scale Invariant Feature Transform and...IJECEIAES
Segmentation of the video sequence by detecting shot changes is essential for video analysis, indexing and retrieval. In this context, a shot boundary detection algorithm is proposed in this paper based on the scale invariant feature transform (SIFT). The first step of our method consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. The overview step provides the locations of boundaries. Secondly, a moving average calculation is performed to determine the type of transition. The proposed method can be used for detecting gradual transitions and abrupt changes without requiring any training of the video content in advance. Experiments have been conducted on a multi type video database and show that this algorithm achieves well performances.
Enhanced Optimization of Edge Detection for High Resolution Images Using Veri...ijcisjournal
dge Detection plays a crucial role in Image Processing and Segmentation where a set of algorithms aims
to identify various portions of a digital image at which a sharpened image is observed in the output or
more formally has discontinuities. The contour of Edge Detection also helps in Object Detection and
Recognition. Image edges can be detected by using two attributes such as Gradient and Laplacian. In our
Paper, we proposed a system which utilizes Canny and Sobel Operators for Edge Detection which is a
Gradient First order derivative function for edge detection by using Verilog Hardware Description
Language and in turn compared with the results of the previous paper in Matlab. The process of edge
detection in Verilog significantly reduces the processing time and filters out unneeded information, while
preserving the important structural properties of an image. This edge detection can be used to detect
vehicles in Traffic Jam, Medical imaging system for analysing MRI, x-rays by using Xilinx ISE Design
Suite 14.2.
Geometric wavelet transform for optical flow estimation algorithmijcga
This paper described an algorithm for computing the optical flow (OF) vector of a moving objet in a video sequence based on geometric wavelet transform (GWT). This method tries to calculate the motion between two successive frames by using a GWT. It consists to project the OF vectors on a basis of geometric wavelet. Using GWT for OF estimation has been attracting much attention. This approach takes advantage of the geometric wavelet filter property and requires only two frames. This algorithm is fast and able to estimate the OF with a low-complexity. The technique is suitable for video compression, and can be used for stereo vision and image registration.
ROLE OF HYBRID LEVEL SET IN FETAL CONTOUR EXTRACTIONsipij
Image processing technologies may be employed for quicker and accurate diagnosis in analysis and
feature extraction of medical images. Here, existing level set algorithm is modified and it is employed for
extracting contour of fetus in an image. In traditional approach, fetal parameters are extracted manually
from ultrasound images. An automatic technique is highly desirable to obtain fetal biometric measurements
due to some problems in traditional approach such as lack of consistency and accuracy. The proposed
approach utilizes global & local region information for fetal contour extraction from ultrasonic images.
The main goal of this research is to develop a new methodology to aid the analysis and feature extraction.
Cracks on the concrete surface are one of the earliest symptoms of degradation of the structure which isfundamental for the upkeep as properly the non-stop publicity will lead to the severe injury to the environment.Manual inspection is the acclaimed approach for the crack inspection. In the guide inspection, the diagram of thecrack is organized manually, and the conditions of the irregularities are noted. Since the guide strategy absolutelyrelies upon on the specialist’s expertise and experience, it lacks objectivity in the quantitative analysis. So,automated image-based crack detection is proposed as a replacement. The proposed gadget comprises pictureprocessing and facts acquisition methodologies for crack detection and evaluation of surface degradation. Theacquired outcomes exhibit that the deployment of image processing in an nice way is a key step towards theinspection of giant infrastructures
Enhanced Face Detection Based on Haar-Like and MB-LBP FeaturesDr. Amarjeet Singh
The effective real-time face detection framework
proposed by Viola and Jones gained much popularity due its
computational efficiency and its simplicity. A notable
variant replaces the original Haar-like features with MBLBP (Multi-Block Local Binary Pattern) which are defined
by the local binary pattern operator, both detector types are
integrated into the OpenCV library. However, each
descriptor and its evaluation method has its own set of
strengths and setbacks. In this paper, an enhanced two-layer
face detector composed of both Haar-like and MB-LBP
features is presented. Haar-like features are employed as a
coarse filter but with a new evaluation involving dual
threshold. The already established MB-LBPs are arranged
as the fine filter of the detector. The Gentle AdaBoost
learning algorithm is deployed for the training of the
proposed detector to reach the classification and
performance potential. Experiments show that in the early
stages of classification, Haar features with dual threshold
are more discriminative than MB-LBP and original Haarlike features with respect to number of features required
and computation. Benchmarking the proposed detector
demonstrate overall 12% higher detection rate at 17% false
alarm over using MB-LBP features singly while performing
with ×3 speedup.
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.
This paper presents crack detection in concrete structure based on fuzzy logic. Safety inspection of concrete structures is very important since it is closely related with the structural health and reliability. Automated structural health monitoring system becomes necessity in recent years that encourages various researches to be going on in this area. Cheap availability of digital cameras makes research work in this field easier. This paper presents digital image processing and fuzzy logic based efficient crack detection technique in concrete structure. Here features from digital image of concrete structure are extracted by using morphological image processing technique and then extracted features are fed to fuzzy logic to accurately identify the crack.
Application of feature point matching to video stabilizationNikhil Prathapani
One of the significant application of computer vision is Stabilizing a video that was captured from a jittery or moving platform. One way to stabilize a video is to track a prominent feature in the image and utilize it as an anchor point to cancel out all perturbations relative to it. This technique, however, must be bootstrapped with knowledge of where such a salient feature remains in the first video frame. The paper presents method of video stabilization that works without any such erstwhile knowledge. The method is built on the basis of Random Sampling and Consensus (RANSAC) and adding few additions to the existing methodologies. It instead automatically investigates for the "background plane" in a video sequence, and utilizes its observed distortion to precise for camera motion. All the simulations have been performed using MATLAB tool.
Object tracking with SURF: ARM-Based platform ImplementationEditor IJCATR
Several algorithms for object tracking, are developed, but our method is slightly different, it’s about how to adapt and implement such algorithms on mobile platform.
We started our work by studying and analyzing feature matching algorithms, to highlight the most appropriate implementation technique for our case.
In this paper, we propose a technique of implementation of the algorithm SURF (Speeded Up Robust Features), for purposes of recognition and object tracking in real time. This is achieved by the realization of an application on a mobile platform such a Raspberry pi, when we can select an image containing the object to be tracked, in the scene captured by the live camera pi. Our algorithm calculates the SURF descriptor for the two images to detect the similarity therebetween, and then matching between similar objects. In the second level, we extend our algorithm to achieve a tracking in real time, all that must respect raspberry pi performances. So, the first thing is setting up all libraries that the raspberry pi need, then adapt the algorithm with card’s performances. This paper presents experimental results on a set of evaluation images as well as images obtained in real time.
2D Features-based Detector and Descriptor Selection System for Hierarchical R...gerogepatton
Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some
methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for
a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical
classification is looking for. We demonstrate that this method performs better than using just one method
like ORB, SIFT or FREAK, despite being fairly slower
2D FEATURES-BASED DETECTOR AND DESCRIPTOR SELECTION SYSTEM FOR HIERARCHICAL R...gerogepatton
Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method
like ORB, SIFT or FREAK, despite being fairly slower.
2D FEATURES-BASED DETECTOR AND DESCRIPTOR SELECTION SYSTEM FOR HIERARCHICAL R...ijaia
Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method like ORB, SIFT or FREAK, despite being fairly slower
Land Boundary Detection of an Island using improved Morphological OperationCSCJournals
Image analysis is one of the important tasks to obtain the information about earth surface. To detect and mark a particular land area, it is required to have the image from remote place. To recognize the same, the accurate boundary of that area has to be detected. In this paper, the example of remote sensing image has been considered. The accurate detection of the boundary is a complex task. A novel method has been proposed in this paper to detect the boundary of such land. Mathematical morphology is a simple and efficient method for this type of task. The morphological analysis is performed using structure elements (SE). By using mathematical morphology the images can be enhanced and then the boundary can be detected easily. Simultaneously the noise is removed by using the proposed model. The results exhibit the performance of the proposed method. Keywords: Remote Sensing images ; Edge detection; Gray- scale Morphological analysis, Structuring Element (SE).
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.
A new approach of edge detection in sar images using region based active cont...eSAT Journals
Abstract This paper presents a new methodology for the edge detection of complex radar images. The approach includes the edge improvisation algorithm and followed with edge detection. The nature of complex radar images made edge enhancement part before the edge detection as the data is highly heterogeneous in nature. Thus, the use of discrete wavelet transform in the edge improvisation algorithm is justified. Then region based active contour model is used as edge detection algorithm. The paper proposes the distribution fitting energy with a level set function and neighborhood means and variances as variables. The performance is tested by applying it on different images and the results are been analyzed. Keywords: Edge detection, Edge improvisation, Synthetic Aperture radar (SAR), wavelet transforms.
The determination of Region-of-Interest has been recognised as an important means by which
unimportant image content can be identified and excluded during image compression or image
modelling, however existing Region-of-Interest detection methods are computationally
expensive thus are mostly unsuitable for managing large number of images and the compression
of images especially for real-time video applications. This paper therefore proposes an
unsupervised algorithm that takes advantage of the high computation speed being offered by
Speeded-Up Robust Features (SURF) and Features from Accelerated Segment Test (FAST) to
achieve fast and efficient Region-of-Interest detection.
Classification and Comparison of License Plates Localization Algorithmssipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
Classification and Comparison of License Plates Localization Algorithmssipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
Classification and Comparison of License Plates Localization Algorithmssipij
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the
application of new information and communication technologies in the transport sector, to make the
infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the
key module of these systems, in which the License Plate Localization (LPL) is the most important stage,
because it determines the speed and robustness of this module. Thus, during this step the algorithm must
process the image and overcome several constraints as climatic and lighting conditions, sensors and angles
variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and
comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages
and improvements made by each of them.
An Assessment of Image Matching Algorithms in Depth EstimationCSCJournals
Computer vision is often used with mobile robot for feature tracking, landmark sensing, and obstacle detection. Almost all high-end robotics systems are now equipped with pairs of cameras arranged to provide depth perception. In stereo vision application, the disparity between the stereo images allows depth estimation within a scene. Detecting conjugate pair in stereo images is a challenging problem known as the correspondence problem. The goal of this research is to assess the performance of SIFT, MSER, and SURF, the well known matching algorithms, in solving the correspondence problem and then in estimating the depth within the scene. The results of each algorithm are evaluated and presented. The conclusion and recommendations for future works, lead towards the improvement of these powerful algorithms to achieve a higher level of efficiency within the scope of their performance.
EFFECTIVE INTEREST REGION ESTIMATION MODEL TO REPRESENT CORNERS FOR IMAGE sipij
One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region
around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new local maxima-based
interest region detection method. This region estimation method can be used to build descriptors to represent corners. We have performed a comparative analysis to match the feature points using recent corner detectors and the result shows that our method achieves better precision and recall results than
existing methods.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Object Capturing In A Cluttered Scene By Using Point Feature MatchingIJERA Editor
Capturing means getting or catching. This project contains an algorithm for capturing a specific target based on the points which corresponds between reference and target image. It can capture the objects in-plane rotation and also effective to small amount of out-of plane rotation also. This method of object capturing works best for objects that exhibit in a cluttered texture patterns, which give rise to unique point feature matches. When a part of object is occluded by other objects in the scene, only features of that part are missed. As long as there are enough features detected in the unoccluded part, the object can captured. The local representation is based on the appearance. There is no need to extract geometric primitives (e.g. lines) which are generally hard to detect reliably.
Hardware Unit for Edge Detection with Comparative Analysis of Different Edge ...paperpublications3
Abstract: An edge in an image is a contour across which the brightness of the image changes abruptly. In image processing, an edge is often interpreted as one class of singularities. Edge detection is an important task in image processing. It is a main tool in pattern recognition, image segmentation, and scene analysis. An edge detector is basically a high pass filter that can be applied to extract the edge points in an image. This topic has attracted many researchers and many achievements have been made. Many researchers provided different approaches based on mathematical calculations which some of them are either robust or cost effective. A new algorithm will be proposed to detect the edges of image with increased robustness and throughput. Using this algorithm we will reduce the time complexity problem which is faced by previous algorithm. We will also propose hardware unit for proposed algorithm which will reduce the area, power and speed problem. We will compare our proposed algorithm with previous approach. For image quality measurement we will use some scientific parameters those are PSNR, SSIM, FSIM. Implementation of proposed algorithm will be done by Matlab and hardware implementation will be done by using of Verilog on Xilinx 14.1 simulator. Verification will be done on Model sim.
Similar to IJERD (www.ijerd.com) International Journal of Engineering Research and Development (20)
A Novel Method for Prevention of Bandwidth Distributed Denial of Service AttacksIJERD Editor
Distributed Denial of Service (DDoS) Attacks became a massive threat to the Internet. Traditional
Architecture of internet is vulnerable to the attacks like DDoS. Attacker primarily acquire his army of Zombies,
then that army will be instructed by the Attacker that when to start an attack and on whom the attack should be
done. In this paper, different techniques which are used to perform DDoS Attacks, Tools that were used to
perform Attacks and Countermeasures in order to detect the attackers and eliminate the Bandwidth Distributed
Denial of Service attacks (B-DDoS) are reviewed. DDoS Attacks were done by using various Flooding
techniques which are used in DDoS attack.
The main purpose of this paper is to design an architecture which can reduce the Bandwidth
Distributed Denial of service Attack and make the victim site or server available for the normal users by
eliminating the zombie machines. Our Primary focus of this paper is to dispute how normal machines are
turning into zombies (Bots), how attack is been initiated, DDoS attack procedure and how an organization can
save their server from being a DDoS victim. In order to present this we implemented a simulated environment
with Cisco switches, Routers, Firewall, some virtual machines and some Attack tools to display a real DDoS
attack. By using Time scheduling, Resource Limiting, System log, Access Control List and some Modular
policy Framework we stopped the attack and identified the Attacker (Bot) machines
Hearing loss is one of the most common human impairments. It is estimated that by year 2015 more
than 700 million people will suffer mild deafness. Most can be helped by hearing aid devices depending on the
severity of their hearing loss. This paper describes the implementation and characterization details of a dual
channel transmitter front end (TFE) for digital hearing aid (DHA) applications that use novel micro
electromechanical- systems (MEMS) audio transducers and ultra-low power-scalable analog-to-digital
converters (ADCs), which enable a very-low form factor, energy-efficient implementation for next-generation
DHA. The contribution of the design is the implementation of the dual channel MEMS microphones and powerscalable
ADC system.
Influence of tensile behaviour of slab on the structural Behaviour of shear c...IJERD Editor
-A composite beam is composed of a steel beam and a slab connected by means of shear connectors
like studs installed on the top flange of the steel beam to form a structure behaving monolithically. This study
analyzes the effects of the tensile behavior of the slab on the structural behavior of the shear connection like slip
stiffness and maximum shear force in composite beams subjected to hogging moment. The results show that the
shear studs located in the crack-concentration zones due to large hogging moments sustain significantly smaller
shear force and slip stiffness than the other zones. Moreover, the reduction of the slip stiffness in the shear
connection appears also to be closely related to the change in the tensile strain of rebar according to the increase
of the load. Further experimental and analytical studies shall be conducted considering variables such as the
reinforcement ratio and the arrangement of shear connectors to achieve efficient design of the shear connection
in composite beams subjected to hogging moment.
Gold prospecting using Remote Sensing ‘A case study of Sudan’IJERD Editor
Gold has been extracted from northeast Africa for more than 5000 years, and this may be the first
place where the metal was extracted. The Arabian-Nubian Shield (ANS) is an exposure of Precambrian
crystalline rocks on the flanks of the Red Sea. The crystalline rocks are mostly Neoproterozoic in age. ANS
includes the nations of Israel, Jordan. Egypt, Saudi Arabia, Sudan, Eritrea, Ethiopia, Yemen, and Somalia.
Arabian Nubian Shield Consists of juvenile continental crest that formed between 900 550 Ma, when intra
oceanic arc welded together along ophiolite decorated arc. Primary Au mineralization probably developed in
association with the growth of intra oceanic arc and evolution of back arc. Multiple episodes of deformation
have obscured the primary metallogenic setting, but at least some of the deposits preserve evidence that they
originate as sea floor massive sulphide deposits.
The Red Sea Hills Region is a vast span of rugged, harsh and inhospitable sector of the Earth with
inimical moon-like terrain, nevertheless since ancient times it is famed to be an abode of gold and was a major
source of wealth for the Pharaohs of ancient Egypt. The Pharaohs old workings have been periodically
rediscovered through time. Recent endeavours by the Geological Research Authority of Sudan led to the
discovery of a score of occurrences with gold and massive sulphide mineralizations. In the nineties of the
previous century the Geological Research Authority of Sudan (GRAS) in cooperation with BRGM utilized
satellite data of Landsat TM using spectral ratio technique to map possible mineralized zones in the Red Sea
Hills of Sudan. The outcome of the study mapped a gossan type gold mineralization. Band ratio technique was
applied to Arbaat area and a signature of alteration zone was detected. The alteration zones are commonly
associated with mineralization. The alteration zones are commonly associated with mineralization. A filed check
confirmed the existence of stock work of gold bearing quartz in the alteration zone. Another type of gold
mineralization that was discovered using remote sensing is the gold associated with metachert in the Atmur
Desert.
Reducing Corrosion Rate by Welding DesignIJERD Editor
The paper addresses the importance of welding design to prevent corrosion at steel. Welding is
used to join pipe, profiles at bridges, spindle, and a lot more part of engineering construction. The
problems happened associated with welding are common issues in these fields, especially corrosion.
Corrosion can be reduced with many methods, they are painting, controlling humidity, and also good
welding design. In the research, it can be found that reducing residual stress on the welding can be
solved in corrosion rate reduction problem.
Preheating on 500oC and 600oC give better condition to reduce corosion rate than condition after
preheating 400oC. For all welding groove type, material with 500oC and 600oC preheating after 14 days
corrosion test is 0,5%-0,69% lost. Material with 400oC preheating after 14 days corrosion test is 0,57%-0,76%
lost.
Welding groove also influence corrosion rate. X and V type welding groove give better condition to reduce
corrosion rate than use 1/2V and 1/2 X welding groove. After 14 days corrosion test, the samples with
X welding groove type is 0,5%-0,57% lost. The samples with V welding groove after 14 days corrosion test is
0,51%-0,59% lost. The samples with 1/2V and 1/2X welding groove after 14 days corrosion test is 0,58%-
0,71% lost.
Router 1X3 – RTL Design and VerificationIJERD Editor
Routing is the process of moving a packet of data from source to destination and enables messages
to pass from one computer to another and eventually reach the target machine. A router is a networking device
that forwards data packets between computer networks. It is connected to two or more data lines from different
networks (as opposed to a network switch, which connects data lines from one single network). This paper,
mainly emphasizes upon the study of router device, it‟s top level architecture, and how various sub-modules of
router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top
module.
Active Power Exchange in Distributed Power-Flow Controller (DPFC) At Third Ha...IJERD Editor
This paper presents a component within the flexible ac-transmission system (FACTS) family, called
distributed power-flow controller (DPFC). The DPFC is derived from the unified power-flow controller (UPFC)
with an eliminated common dc link. The DPFC has the same control capabilities as the UPFC, which comprise
the adjustment of the line impedance, the transmission angle, and the bus voltage. The active power exchange
between the shunt and series converters, which is through the common dc link in the UPFC, is now through the
transmission lines at the third-harmonic frequency. DPFC multiple small-size single-phase converters which
reduces the cost of equipment, no voltage isolation between phases, increases redundancy and there by
reliability increases. The principle and analysis of the DPFC are presented in this paper and the corresponding
simulation results that are carried out on a scaled prototype are also shown.
Mitigation of Voltage Sag/Swell with Fuzzy Control Reduced Rating DVRIJERD Editor
Power quality has been an issue that is becoming increasingly pivotal in industrial electricity
consumers point of view in recent times. Modern industries employ Sensitive power electronic equipments,
control devices and non-linear loads as part of automated processes to increase energy efficiency and
productivity. Voltage disturbances are the most common power quality problem due to this the use of a large
numbers of sophisticated and sensitive electronic equipment in industrial systems is increased. This paper
discusses the design and simulation of dynamic voltage restorer for improvement of power quality and
reduce the harmonics distortion of sensitive loads. Power quality problem is occurring at non-standard
voltage, current and frequency. Electronic devices are very sensitive loads. In power system voltage sag,
swell, flicker and harmonics are some of the problem to the sensitive load. The compensation capability
of a DVR depends primarily on the maximum voltage injection ability and the amount of stored
energy available within the restorer. This device is connected in series with the distribution feeder at
medium voltage. A fuzzy logic control is used to produce the gate pulses for control circuit of DVR and the
circuit is simulated by using MATLAB/SIMULINK software.
Study on the Fused Deposition Modelling In Additive ManufacturingIJERD Editor
Additive manufacturing process, also popularly known as 3-D printing, is a process where a product
is created in a succession of layers. It is based on a novel materials incremental manufacturing philosophy.
Unlike conventional manufacturing processes where material is removed from a given work price to derive the
final shape of a product, 3-D printing develops the product from scratch thus obviating the necessity to cut away
materials. This prevents wastage of raw materials. Commonly used raw materials for the process are ABS
plastic, PLA and nylon. Recently the use of gold, bronze and wood has also been implemented. The complexity
factor of this process is 0% as in any object of any shape and size can be manufactured.
Spyware triggering system by particular string valueIJERD Editor
This computer programme can be used for good and bad purpose in hacking or in any general
purpose. We can say it is next step for hacking techniques such as keylogger and spyware. Once in this system if
user or hacker store particular string as a input after that software continually compare typing activity of user
with that stored string and if it is match then launch spyware programme.
A Blind Steganalysis on JPEG Gray Level Image Based on Statistical Features a...IJERD Editor
This paper presents a blind steganalysis technique to effectively attack the JPEG steganographic
schemes i.e. Jsteg, F5, Outguess and DWT Based. The proposed method exploits the correlations between
block-DCTcoefficients from intra-block and inter-block relation and the statistical moments of characteristic
functions of the test image is selected as features. The features are extracted from the BDCT JPEG 2-array.
Support Vector Machine with cross-validation is implemented for the classification.The proposed scheme gives
improved outcome in attacking.
Secure Image Transmission for Cloud Storage System Using Hybrid SchemeIJERD Editor
- Data over the cloud is transferred or transmitted between servers and users. Privacy of that
data is very important as it belongs to personal information. If data get hacked by the hacker, can be
used to defame a person’s social data. Sometimes delay are held during data transmission. i.e. Mobile
communication, bandwidth is low. Hence compression algorithms are proposed for fast and efficient
transmission, encryption is used for security purposes and blurring is used by providing additional
layers of security. These algorithms are hybridized for having a robust and efficient security and
transmission over cloud storage system.
Application of Buckley-Leverett Equation in Modeling the Radius of Invasion i...IJERD Editor
A thorough review of existing literature indicates that the Buckley-Leverett equation only analyzes
waterflood practices directly without any adjustments on real reservoir scenarios. By doing so, quite a number
of errors are introduced into these analyses. Also, for most waterflood scenarios, a radial investigation is more
appropriate than a simplified linear system. This study investigates the adoption of the Buckley-Leverett
equation to estimate the radius invasion of the displacing fluid during waterflooding. The model is also adopted
for a Microbial flood and a comparative analysis is conducted for both waterflooding and microbial flooding.
Results shown from the analysis doesn’t only records a success in determining the radial distance of the leading
edge of water during the flooding process, but also gives a clearer understanding of the applicability of
microbes to enhance oil production through in-situ production of bio-products like bio surfactans, biogenic
gases, bio acids etc.
Gesture Gaming on the World Wide Web Using an Ordinary Web CameraIJERD Editor
- Gesture gaming is a method by which users having a laptop/pc/x-box play games using natural or
bodily gestures. This paper presents a way of playing free flash games on the internet using an ordinary webcam
with the help of open source technologies. Emphasis in human activity recognition is given on the pose
estimation and the consistency in the pose of the player. These are estimated with the help of an ordinary web
camera having different resolutions from VGA to 20mps. Our work involved giving a 10 second documentary to
the user on how to play a particular game using gestures and what are the various kinds of gestures that can be
performed in front of the system. The initial inputs of the RGB values for the gesture component is obtained by
instructing the user to place his component in a red box in about 10 seconds after the short documentary before
the game is finished. Later the system opens the concerned game on the internet on popular flash game sites like
miniclip, games arcade, GameStop etc and loads the game clicking at various places and brings the state to a
place where the user is to perform only gestures to start playing the game. At any point of time the user can call
off the game by hitting the esc key and the program will release all of the controls and return to the desktop. It
was noted that the results obtained using an ordinary webcam matched that of the Kinect and the users could
relive the gaming experience of the free flash games on the net. Therefore effective in game advertising could
also be achieved thus resulting in a disruptive growth to the advertising firms.
Hardware Analysis of Resonant Frequency Converter Using Isolated Circuits And...IJERD Editor
-LLC resonant frequency converter is basically a combo of series as well as parallel resonant ckt. For
LCC resonant converter it is associated with a disadvantage that, though it has two resonant frequencies, the
lower resonant frequency is in ZCS region[5]. For this application, we are not able to design the converter
working at this resonant frequency. LLC resonant converter existed for a very long time but because of
unknown characteristic of this converter it was used as a series resonant converter with basically a passive
(resistive) load. . Here, it was designed to operate in switching frequency higher than resonant frequency of the
series resonant tank of Lr and Cr converter acts very similar to Series Resonant Converter. The benefit of LLC
resonant converter is narrow switching frequency range with light load[6] . Basically, the control ckt plays a
very imp. role and hence 555 Timer used here provides a perfect square wave as the control ckt provides no
slew rate which makes the square wave really strong and impenetrable. The dead band circuit provides the
exclusive dead band in micro seconds so as to avoid the simultaneous firing of two pairs of IGBT’s where one
pair switches off and the other on for a slightest period of time. Hence, the isolator ckt here is associated with
each and every ckt used because it acts as a driver and an isolation to each of the IGBT is provided with one
exclusive transformer supply[3]. The IGBT’s are fired using the appropriate signal using the previous boards
and hence at last a high frequency rectifier ckt with a filtering capacitor is used to get an exact dc
waveform .The basic goal of this particular analysis is to observe the wave forms and characteristics of
converters with differently positioned passive elements in the form of tank circuits.
Simulated Analysis of Resonant Frequency Converter Using Different Tank Circu...IJERD Editor
LLC resonant frequency converter is basically a combo of series as well as parallel resonant ckt. For
LCC resonant converter it is associated with a disadvantage that, though it has two resonant frequencies, the
lower resonant frequency is in ZCS region [5]. For this application, we are not able to design the converter
working at this resonant frequency. LLC resonant converter existed for a very long time but because of
unknown characteristic of this converter it was used as a series resonant converter with basically a passive
(resistive) load. . Here, it was designed to operate in switching frequency higher than resonant frequency of the
series resonant tank of Lr and Cr converter acts very similar to Series Resonant Converter. The benefit of LLC
resonant converter is narrow switching frequency range with light load[6] . Basically, the control ckt plays a
very imp. role and hence 555 Timer used here provides a perfect square wave as the control ckt provides no
slew rate which makes the square wave really strong and impenetrable. The dead band circuit provides the
exclusive dead band in micro seconds so as to avoid the simultaneous firing of two pairs of IGBT’s where one
pair switches off and the other on for a slightest period of time. Hence, the isolator ckt here is associated with
each and every ckt used because it acts as a driver and an isolation to each of the IGBT is provided with one
exclusive transformer supply[3]. The IGBT’s are fired using the appropriate signal using the previous boards
and hence at last a high frequency rectifier ckt with a filtering capacitor is used to get an exact dc
waveform .The basic goal of this particular analysis is to observe the wave forms and characteristics of
converters with differently positioned passive elements in the form of tank circuits. The supported simulation
is done through PSIM 6.0 software tool
Amateurs Radio operator, also known as HAM communicates with other HAMs through Radio
waves. Wireless communication in which Moon is used as natural satellite is called Moon-bounce or EME
(Earth -Moon-Earth) technique. Long distance communication (DXing) using Very High Frequency (VHF)
operated amateur HAM radio was difficult. Even with the modest setup having good transceiver, power
amplifier and high gain antenna with high directivity, VHF DXing is possible. Generally 2X11 YAGI antenna
along with rotor to set horizontal and vertical angle is used. Moon tracking software gives exact location,
visibility of Moon at both the stations and other vital data to acquire real time position of moon.
“MS-Extractor: An Innovative Approach to Extract Microsatellites on „Y‟ Chrom...IJERD Editor
Simple Sequence Repeats (SSR), also known as Microsatellites, have been extensively used as
molecular markers due to their abundance and high degree of polymorphism. The nucleotide sequences of
polymorphic forms of the same gene should be 99.9% identical. So, Microsatellites extraction from the Gene is
crucial. However, Microsatellites repeat count is compared, if they differ largely, he has some disorder. The Y
chromosome likely contains 50 to 60 genes that provide instructions for making proteins. Because only males
have the Y chromosome, the genes on this chromosome tend to be involved in male sex determination and
development. Several Microsatellite Extractors exist and they fail to extract microsatellites on large data sets of
giga bytes and tera bytes in size. The proposed tool “MS-Extractor: An Innovative Approach to extract
Microsatellites on „Y‟ Chromosome” can extract both Perfect as well as Imperfect Microsatellites from large
data sets of human genome „Y‟. The proposed system uses string matching with sliding window approach to
locate Microsatellites and extracts them.
Importance of Measurements in Smart GridIJERD Editor
- The need to get reliable supply, independence from fossil fuels, and capability to provide clean
energy at a fixed and lower cost, the existing power grid structure is transforming into Smart Grid. The
development of a smart energy distribution grid is a current goal of many nations. A Smart Grid should have
new capabilities such as self-healing, high reliability, energy management, and real-time pricing. This new era
of smart future grid will lead to major changes in existing technologies at generation, transmission and
distribution levels. The incorporation of renewable energy resources and distribution generators in the existing
grid will increase the complexity, optimization problems and instability of the system. This will lead to a
paradigm shift in the instrumentation and control requirements for Smart Grids for high quality, stable and
reliable electricity supply of power. The monitoring of the grid system state and stability relies on the
availability of reliable measurement of data. In this paper the measurement areas that highlight new
measurement challenges, development of the Smart Meters and the critical parameters of electric energy to be
monitored for improving the reliability of power systems has been discussed.
Study of Macro level Properties of SCC using GGBS and Lime stone powderIJERD Editor
One of the major environmental concerns is the disposal of the waste materials and utilization of
industrial by products. Lime stone quarries will produce millions of tons waste dust powder every year. Having
considerable high degree of fineness in comparision to cement this material may be utilized as a partial
replacement to cement. For this purpose an experiment is conducted to investigate the possibility of using lime
stone powder in the production of SCC with combined use GGBS and how it affects the fresh and mechanical
properties of SCC. First SCC is made by replacing cement with GGBS in percentages like 10, 20, 30, 40, 50 and
by taking the optimum mix with GGBS lime stone powder is blended to mix in percentages like 5, 10, 15, 20 as
a partial replacement to cement. Test results shows that the SCC mix with combination of 30% GGBS and 15%
limestone powder gives maximum compressive strength and fresh properties are also in the limits prescribed by
the EFNARC.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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IJERD (www.ijerd.com) International Journal of Engineering Research and Development
1. International Journal of Engineering Research and Development
e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com
Volume 2, Issue 12 (August 2012), PP. 07-12
Analysis and Classification of Feature Extraction Techniques: A
Study
Shubha Bhat1, Vindhya P Malagi2, Ramesh Babu D R3, Ramakrishna K A4
1,2,3,4
Computer Science and Engineering Department, Dayananda Sagar College of Engineering, Bangalore, India
Abstract––A detailed study on feature extractors in spatial and transformed domain is carried out in this work. The
survey in Spatial domain include most of the traditional detectors until recently the SIFT and its variants. In the
transformed domain, the detectors developed using the Fourier transforms to wavelet transforms have been explored. The
advantages and the limitations of each one of them is explained along with the results. Depending upon the application in
hand together with time complexity and accuracy, an appropriate choice of the suitable detector has to be made.
Keywords––Localization; Keypoints; Scale Invariant Feature Transform; Fourier transform; Dual-Tree Complex
Wavelet Transform
I. INTRODUCTION
Features are distinguishable properties or characteristics of an image. Distinct areas of interest such as an edge,
corner or a contour can be considered as features in an image. There exist two groups of techniques in the literature for feature
extraction. One is based on the localization of features in a sub image and the second global analysis of the entire image. The
first approach derives the knowledge about the environment from geometric conditions for example obtained from the
odometric measurements of the camera motion or information obtained from a pair of stereo cameras. In this case, the region
of interest is a small patch or sub-image within the whole image. Whereas, the Global approach derives its information about
the environment based on the information spread out over the entire image. The entire image as a whole is considered the
region of interest.
Edge detection is an important task in feature extraction. It is a main tool in several applications for pattern
recognition, image segmentation and scene analysis. An edge in an image is a contour across which the brightness of the
image changes abruptly. In image processing, an edge is often interpreted as one class of singularities. In a function,
singularities can be characterized easily as discontinuities where the gradient approaches infinity. However, image data is
discrete, so edges in an image often are defined as the local maxima of the gradient. An edge detector is basically a high-pass
filter that can be applied to extract the edge points in an image. This topic has attracted many researchers and many
achievements have been made.
In addition to edges, the corners are also considered the best features that can be extracted from an image. Other than
edges and corners, blobs are also the best candidates for extracting salient features in an image. Blobs are regions in the image
that may contain objects of interest and are either brighter or darker than its surroundings. There are several techniques
reported in the literature to detect blobs. Some of the approaches employed to detect blobs are Laplacian of Gaussian (LoG),
Difference of Gaussian (DoG), Determinant of Hessian etc which are chosen aptly for the desired application.
In this study, the feature detection methods preferably the edges and the corners as point detectors in the spatial and
transformed domains are explored from the vast literature.
The remainder of the paper is as follows: in Section II, a detailed survey in spatial domain is carried out. Section III
explains the feature extraction techniques in transformed domain with results in the respective sections. Finally the study
concludes with Section IV.
II. FEATURE DETECTION – SPATIAL DOMAIN
The following section explains in detail the traditional methods beginning with the work of canny and harris until
recently the revolutionary work of Lowe [17] and its various variants in spatial domain.
A. Traditional feature extraction methods
The earliest work on feature extraction trace back to the year 1979 when Moravec first introduced the term ’interest
points’ [1]. Later many variations came into existence on the computation of interest points, followed with the pioneering
work of Harris and Stephens [2]. The Harris-Laplace and Hessian-Laplace region detectors [3][4] are considered invariant to
rotation and scale changes. Some moment-based region detectors [5][6] include Harris-Affine and Hessian-Affine region
detectors [7][8]. Others include an edge-based region detector [9], an intensity- based region detector [10], an entropy-based
region detector [11] and two independently developed level line-based region detectors called the MSER (Maximally Stable
Extremal Region) [12] and LLD (Level Line Descriptor) [13] [14] [15]. These are designed to be invariant to affine
transformations. These two methods stem from the Monasse image registration method [16] that uses well contrasted extremal
regions to register images. It is reported that MSER is the most efficient one and has better performance than other affine
invariant detectors [12]. However, as pointed out in [16], no known detector is actually fully affine invariant. All of them start
7
2. Analysis and Classification of Feature Extraction Techniques: A Study
with initial feature scales and locations selected in a non-affine invariant manner. The difficulty comes from the scale change
from an image to another. This change of scale is actually an under-sampling, which means that the images differ by a blur.
It is found that the traditional methods in the spatial domain like canny, sobel, prewitt, roberts etc are simplistic
and straight-forward in extracting and matching the image features. However it is observed that either too much of irrelevant
information is provided making it slower or some of the useful information (prominent features) is lost. Further study in the
spatial domain moves on to the famous state-of-the-art technique called the SIFT (scale-invariant feature transform)
developed by David Lowe in 1999.
B. SIFT
Lowe in [17], has addressed the problem of affine invariance for feature extraction and proposed the so called scale-
invariant feature transform (SIFT) descriptor, that is invariant to image translations and rotations, to scale changes (blur), and
robust to illumination changes. It is also robust to orientation changes of the viewpoint up to 60 degrees. This approach has
been named the Scale Invariant Feature Transform (SIFT), as it transforms image data into scale-invariant coordinates relative
to local features. This methodology can perform the above mentioned steps either in spatial or in frequency domain. The study
in the frequency domain is explained later in section III. The Fig. 1 below shows the features detected by traditional detectors
starting from canny to SIFT in the spatial domain for an aerial image.
Fig. 1. Features detected using various traditional spatial domain detectors on an aerial image.
The edges and feature points extracted from various detectors shown in the Fig. 1 above reveal canny detector
(Fig.1b) still remains the best edge detector. However, it is also seen that SIFT (Fig. 1h) detects local features of interest rather
than extracting the entire continuum making it computationally efficient. Based on the scale space theory [18], the SIFT
procedure simulates all Gaussian blurs and normalizes local patches around scale covariant image key points that are
Laplacian extreme.
A number of SIFT variants and extensions including PCA-SIFT [19] and gradient location-orientation histogram
(GLOH) [20] claim to have better robustness and distinctiveness with scaled-down complexity and have been improved with
every version with respect to accuracy or time complexity [21] [22]. Several variants of SIFT are explained further.
1) PCA-SIFT
Principal Component Analysis-SIFT [19]: This is an alternate representation for local image descriptors for the SIFT
algorithm. Compared to the standard representation, PCA-SIFT is both more distinctive and more compact leading to
significant improvements in matching accuracy and speed for both controlled and real-world conditions. Although PCA is ill
suited for representing the general class of image patches, it is very well-suited for capturing the variation in the gradient
image of a keypoint that has been localized in scale, space and orientation. The work in [19] is extended to the color images.
Further exploration in the same is carried out by the authors of PCA-SIFT to other keypoint algorithms.
2) ASIFT
The method proposed, affine-SIFT (ASIFT) [24], simulates all image views obtainable by varying the two camera
axis orientation parameters, namely, the latitude and the longitude angles, left over by the SIFT method. Then it covers the
other four parameters by using the SIFT method itself.
3) A2SIFT
With Lowe’s implementation as the basis, Auto-Adaptive SIFT [25] improves the performance further. The
technique allows extraction of homologous points not only in high geometric distortions but also over bad textured images,
where the traditional implementation generally fails. A2 SIFT can be effectively used in aerial photogrammetric applications.
4) SURF
8
3. Analysis and Classification of Feature Extraction Techniques: A Study
The Speeded Up Robust Features [23] developed by Bay et al, is a faster implementation compared to the other
variants. It is also scale and rotation invariant interest point descriptor and detector. The important speed gain is due to the
integration of images, which drastically reduce the number of operations for small box convolutions, independent of the
chosen scale. Even without any dedicated optimizations, real time computation has been achieved without any loss in
performance.
III. FEATURE DETECTION – TRANSFORMED DOMAIN
Further in the transformed domain, study of feature detection techniques using Fourier transforms and other
transforms is carried out.
A. Fourier transforms
In the Fourier domain, the high frequency content are the edges and other significant features in the image.
Normally a high pass filter is employed to extract out high frequency content of the signal. The filter allows the high frequency
content to pass through while throwing out the low frequency content (less prominent features) of the image. Fourier
transforms and its variants, have great ability to capture the frequency content of the image and convert it back to spatial
domain using inverse transform very efficiently without losing any information. However, the whole image (global) is spread
over the entire frequency axis limiting it from the localization of the image features both in space and frequency
simultaneously.
The main drawback of Fourier analysis is that the function is defined from -∞ to ∞ . The effects of each frequency
are analyzed as if they were spread over the entire signal. In general, this is not the case. Usually an image is continuously
varying in frequency (grey scale information in spatial domain). Fourier analysis done on the image tells us which frequencies
exist, but not where they are.
B. Short term Fourier transforms
However, the short time Fourier transform (STFT) is slightly better over Fourier transforms. They often are used
when the frequencies of the signal vary greatly with time using different windows but of fixed size. When larger windows are
used, lower frequencies can be detected, but their position in time is less certain. With a smaller window, the position can be
determined with greater accuracy, but lower frequencies will not be detected. This is the main disadvantage of STFT.
Here, the Wavelets solve this problem. Once applied to a function f(t), it provides a set of functions Ws f(t). Each
function describes the strength of a wavelet scaled by factor s at time t. The wavelet extends for only a short period, so its
effects are limited to the area immediately surrounding t. The wavelet transform will give information about the strengths of
the frequencies of a signal at time t.
Significant contributions were done in the frequency domain [26] by Peter Kovesi, who proposed the concept of
Phase Congruency to determine the features in the image. This technique is invariant to illumination and contrast. The image
features such as step edges, lines, and Mach bands all give rise to points where the Fourier components of the image are
maximally in phase. The use of phase congruency for marking features has found significant advantages over gradient-based
methods.
Further, Luca Lucchese in [27] proposed an algorithm in frequency domain that efficiently determines the affine
transformations so as to model the relations between pairs of images. This paper presents a new frequency domain technique
for estimating affine transformations. It consists of two main steps, one the affine matrix is first estimated and second after
compensating for the contribution of the affine matrix, the translation vector is then recovered by means of standard phase
correlation. Experimental evidence of the effectiveness of this technique has also been reported and discussed.
C. Discrete Wavelet transforms
In the wavelet domain, Literature shows some interesting work for feature extraction and matching. In [28], the
authors have proposed a method to detect edges of the given image using 2-D wavelet transform. This method uses the
discrete wavelet transform (DWT) to decompose the image into sub-images, details and an approximation.
Further variants of wavelets and related families show significant advances in area of Feature Detection. In [29], the
authors explore the directional extension of multidimensional wavelet transforms, called “contourlets”, to perform pattern
recognition. The general concept of a directional extension vs. a regular multidimensional wavelet transform is discussed
along with the reasoning behind the directional extension. Then, a comparison is done using sample images between the
contourlet transform and other edge detection methods for feature detection.
The authors in this paper [30] propose a new technique wherein the feature’s (edge points) response is maximum in
its neighborhood. The directions of the edges are also estimated from the edge outputs using a line-fitting model. The
orientation (rotation angle) of the edges is estimated using angle histograms. The matching of the images is done based on this
rotation angle. The authors have proven that translational and rotational changes do not cause much impact, whereas, scaling
effect is tolerated up to 10%, beyond which the algorithm restricts itself. The authors claim that the algorithm is faster and
more reliable than the conventional methods.
The initial study was conducted to explore all the variants of Wavelets available in the literature. The traditional
Discrete Wavelet transform (DWT) was found well suited for image compression and denoising kind of applications due to its
multi-scale and multi-resolution characteristics. However, it was seen that it suffered from poor directionality, shift sensitivity
and lack of phase information. The other variants of wavelets such as the Wedgelets, Curvelets, Contourlets etc, in spite of
their multiscaling features, lacked one or the other characteristics mentioned above. Moreover, what is reported so far in the
literature is the usage of these techniques in the context of image compression, texture synthesis etc.
9
4. Analysis and Classification of Feature Extraction Techniques: A Study
D. Complex Wavelet transforms
The above mentioned limitations of discrete wavelets were overcome by another variant of wavelets called the Dual-
tree Complex Wavelet Transforms. The use of complex wavelets in image processing was originally set up in 1995 by J.M.
Lina and Gagnon L in the framework of the Daubechies orthogonal filters banks. It was then generalized in 1997 by Prof. Nick
Kingsbury of Cambridge University.
The fundamental paper [31] from Prof. Nick Kingsbury and his team on Keypoint detection using dual-tree complex
wavelets is been a ground breaking. The paper shows that DTCWT is a well-suited basis for this problem, as it is directionally
selective, smoothly shift invariant, optimally decimated at coarse scales and invertible (no loss of information). The authors
claim that their scheme is fast because of the decimated nature of the DTCWT and yet provides accurate and robust keypoint
localization, together with the use of the “accumulated energy map”. Furthermore results show better robustness against
rotation compared to the SIFT detector. Hence the choice of DTCWT would be a best option over any of its contemporary
methods.
Fig. 2. Features detected using various transformed domain detectors on an aerial image.
Fig. 2 above shows features detected in the transformed domain. The DTCWT features detected here are
predominant local interest points wherein their orientation is also taken of. Again, the number of feature keypoints detected
are sufficient enough for performing correspondence and registration of images.
The comparison of the different feature extraction techniques explained in the entire paper are summarized in the
Table 1 shown below. Here, the column heads T, R, S, L, TC and RE represents respectively the Translation invariance,
Rotational invariance, Scale invariance, Localization, time complexity and Reliability as evaluation measures. Thus, one has
to suitably choose the best detector as per the requirements of the application in hand.
TABLE 1 : EVALUATION OF EXISTING FEATURE EXTRACTION TECHNIQUES IN SPATIAL AND TRANSFORMED DOMAIN
Legend: ++ Very Good, + Good, - fair, - - poor
Technique T R S L TC RE
Spatial domain techniques (eg, SIFT) ++ + ++ ++ - -
Frequency Domain techniques (eg, Fourier) + + + -- + --
Wavelet techniques - - ++ ++ - -
(eg, Discrete Wavelet Transform)
Complex Wavelet techniques (eg, Dual-tree complex ++ ++ ++ ++ - +
Wavelet Transform)
(Comparison based on our survey and experiments)
IV. OBSERVATIONS AND CONCLUSION
The study explores the different spatial and transformed domain approaches to feature extraction. In the literature, it
is claimed that SIFT is one of the most robust technique used to detect and match features between images. It is invariant to
image translations and rotations, to scale changes, robust to illumination changes and also robust to a certain extent to
orientation changes of the viewpoint. Although it a robust method, most of the tasks are computationally intensive and
cumbersome. Whereas in this study, the focus is on transformed domain techniques in order to speed up certain functionalities
compared to spatial approaches. Further in the study, other frequency and wavelet domain methods to detect features are
explored.
10
5. Analysis and Classification of Feature Extraction Techniques: A Study
The Wavelet approach alternatively leverages the strengths of both spatial and frequency domain processing. The
image information can be viewed and processed in both space as well as frequency domains simultaneously. It has an added
advantage of representing the image in multiple scales and multiresolutions. Thus, working in the Wavelet domain becomes
interesting to explore both spatio-frequency characteristics of the image.
The Complex Wavelets Transforms (CWT) use complex-valued filtering (analytic filter) that decomposes the
real/complex signals into real and imaginary parts in transform domain. The real and imaginary coefficients are used to
compute amplitude and phase information respectively in addition to the above mentioned characteristics of shift, rotation
and scale invariance, just the type of information needed to accurately describe the energy localization of oscillating
functions (wavelet basis).
Thus the choice of appropriate detector always should consider the application in hand. Further, appropriate
tradeoff between computational time and accuracy in detecting the interest features should also be considered.
ACKNOWLEDGMENT
This work has been funded by ER&IPR Grand-in-Aid Research Project ERIP/ER/0904468/M/01/1181 of DRDO.
The authors would like to thank Dr S Sankaran, Director ER&IPR HQ for all his encouragement and support. The authors
would specially like to thank Shri P.S Krishanan, Director, Shri V.S Chandrashekar, Group Director and Ms Neeta Trivedi,
Head, AIEL of ADE, DRDO for their constant help and support. The authors are thankful to Dr. Krishnan, professor at CSE,
DSCE, Bangalore for his technical help and support.
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