Video Stabilization, which is important for better analysis and user experience, is typically done through Global Motion Estimation (GME) and Compensation. GME can be done in image domain using many techniques or in Transform domain using the well-known Phase Correlation methods which relate motion to phase shift in the spectrum. While image domain methods are generally slower (due to dense vector field computations), they can do global as well as local motion estimation. Transform domain methods cannot normally do local motion, but are faster and more accurate on homogeneous images, and are resilient to even rapid illumination changes and large motion. However both these approaches can become very time consuming if one needs more accuracy and smoothness because of the nature of the tradeoff. We show here that wavelet transforms can be used in a novel way to achieve a very smooth stabilization along with a significant speedup in this Fourier domain computation without sacrificing accuracy. We
do this by adaptively selecting and combining motion computed on a specific pair of sub-bands using the wavelet interpolation capability. Our approach yields a smooth, scalable, fast and
adaptive algorithm (based on time requirement and recent motion history) to yield significantly better accuracy than a single level wavelet decomposition based approach.
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.
Segmentation Based Multilevel Wide Band Compression for SAR Images Using Coif...CSCJournals
Synthetic aperture radar (SAR) data represents a significant resource of information for a large variety of researchers. Thus, there is a strong interest in developing data encoding and decoding algorithms which can obtain higher compression ratios while keeping image quality to an acceptable level. In this work, results of different wavelet-based image compression and segmentation based wavelet image compression are assessed through controlled experiments on synthetic SAR images. The effects of dissimilar wavelet functions, number of decompositions are examined in order to find optimal family for SAR images. The choice of optimal wavelets in segmentation based wavelet image compression is coiflet for low frequency and high frequency component. The results presented here is a good reference for SAR application developers to choose the wavelet families and also it concludes that wavelets transform is rapid, robust and reliable tool for SAR image compression. Numerical results confirm the potency of this approach.
COMPLEMENTARY VISION BASED DATA FUSION FOR ROBUST POSITIONING AND DIRECTED FL...ijaia
The present paper describes an improved 4 DOF (x/y/z/yaw) vision based positioning solution for fully 6
DOF autonomous UAVs, optimised in terms of computation and development costs as well as robustness
and performance. The positioning system combines Fourier transform-based image registration (Fourier
Tracking) and differential optical flow computation to overcome the drawbacks of a single approach. The
first method is capable of recognizing movement in four degree of freedom under variable lighting conditions, but suffers from low sample rate and high computational costs. Differential optical flow computation, on the other hand, enables a very high sample rate to gain control robustness. This method, however, is limited to translational movement only and performs poor in bad lighting conditions. A reliable positioning system for autonomous flights with free heading is obtained by fusing both techniques. Although the vision system can measure the variable altitude during flight, infrared and ultrasonic sensors are used for robustness. This work is part of the AQopterI8 project, which aims to develop an autonomous
flying quadrocopter for indoor application and makes autonomous directed flight possible.
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.
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.
Segmentation Based Multilevel Wide Band Compression for SAR Images Using Coif...CSCJournals
Synthetic aperture radar (SAR) data represents a significant resource of information for a large variety of researchers. Thus, there is a strong interest in developing data encoding and decoding algorithms which can obtain higher compression ratios while keeping image quality to an acceptable level. In this work, results of different wavelet-based image compression and segmentation based wavelet image compression are assessed through controlled experiments on synthetic SAR images. The effects of dissimilar wavelet functions, number of decompositions are examined in order to find optimal family for SAR images. The choice of optimal wavelets in segmentation based wavelet image compression is coiflet for low frequency and high frequency component. The results presented here is a good reference for SAR application developers to choose the wavelet families and also it concludes that wavelets transform is rapid, robust and reliable tool for SAR image compression. Numerical results confirm the potency of this approach.
COMPLEMENTARY VISION BASED DATA FUSION FOR ROBUST POSITIONING AND DIRECTED FL...ijaia
The present paper describes an improved 4 DOF (x/y/z/yaw) vision based positioning solution for fully 6
DOF autonomous UAVs, optimised in terms of computation and development costs as well as robustness
and performance. The positioning system combines Fourier transform-based image registration (Fourier
Tracking) and differential optical flow computation to overcome the drawbacks of a single approach. The
first method is capable of recognizing movement in four degree of freedom under variable lighting conditions, but suffers from low sample rate and high computational costs. Differential optical flow computation, on the other hand, enables a very high sample rate to gain control robustness. This method, however, is limited to translational movement only and performs poor in bad lighting conditions. A reliable positioning system for autonomous flights with free heading is obtained by fusing both techniques. Although the vision system can measure the variable altitude during flight, infrared and ultrasonic sensors are used for robustness. This work is part of the AQopterI8 project, which aims to develop an autonomous
flying quadrocopter for indoor application and makes autonomous directed flight possible.
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.
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 ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
Currently, in both market and the academic communities have required applications based on image and video processing with several real-time constraints. On the other hand, detection of moving objects is a very important task in mobile robotics and surveillance applications. In order to achieve this, we are using a alternative means for real time motion detection systems. This paper proposes hardware architecture for motion detection based on the background subtraction algorithm, which is implemented on FPGAs (Field Programmable Gate Arrays). For achieving this, the following steps are executed: (a) a background image (in gray-level format) is stored in an external SRAM memory, (b) a low-pass filter is applied to both the stored and current images, (c) a subtraction operation between both images is obtained, and (d) a morphological filter is applied over the resulting image. Afterward, the gravity center of the object is calculated and sent to a PC (via RS-232 interface).
HUMAN ACTION RECOGNITION IN VIDEOS USING STABLE FEATURES sipij
Human action recognition is still a challenging problem and researchers are focusing to investigate this
problem using different techniques. We propose a robust approach for human action recognition. This is
achieved by extracting stable spatio-temporal features in terms of pairwise local binary pattern (P-LBP)
and scale invariant feature transform (SIFT). These features are used to train an MLP neural network
during the training stage, and the action classes are inferred from the test videos during the testing stage.
The proposed features well match the motion of individuals and their consistency, and accuracy is higher
using a challenging dataset. The experimental evaluation is conducted on a benchmark dataset commonly
used for human action recognition. In addition, we show that our approach outperforms individual features
i.e. considering only spatial and only temporal feature.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Motion Detection and Clustering Using PCA and NN in Color Image SequenceTELKOMNIKA JOURNAL
This paper presents a motion detection method with the use of the Principal Component
Analysis. This method is able to detect and track moving objects in a sequence of images. The tested
sequence is segmented within the meaning of movement. In this paper, the concept of extracting
significant information from a large number of data is adopted to provide an effective method for tracking
moving objects on the video image. The principal components are different in term of getting significant
information, the nature of motion (the nature of information) is responsible of this difference, the algorithm
in this paper distinguish the motion nature and choose the appropriate components to give a best
segmentation.
Modified Adaptive Lifting Structure Of CDF 9/7 Wavelet With Spiht For Lossy I...idescitation
We present a modified structure of 2-D cdf 9/7 wavelet
transforms based on adaptive lifting in image coding. Instead
of alternately applying horizontal and vertical lifting, as in
present practice, Adaptive lifting performs lifting-based
prediction in local windows in the direction of high pixel
correlation. Hence, it adapts far better to the image orientation
features in local windows. The predicting and updating signals
of Adaptive lifting can be derived even at the fractional pixel
precision level to achieve high resolution, while still
maintaining perfect reconstruction. To enhance the
performance of adaptive based modified structure of 2-D CDF
9/7 is coupled with SPIHT coding algorithm to improve the
drawbacks of wavelet transform. Experimental results show
that the proposed modified scheme based image coding
technique outperforms JPEG 2000 in both PSNR and visual
quality, with the improvement up to 6.0 dB than existing
structure on images with rich orientation features .
Introduction to Wavelet Transform and Two Stage Image DE noising Using Princi...ijsrd.com
In past two decades there are various techniques are developed to support variety of image processing applications. The applications of image processing include medical, satellite, space, transmission and storage, radar and sonar etc. But noise in image effect all applications. So it is necessary to remove noise from image. There are various methods and techniques are there to remove noise from images. Wavelet transform (WT) has been proved to be effective in noise removal but this have some problems that is overcome by PCA method. This paper presents an efficient image de-noising scheme by using principal component analysis (PCA) with local pixel grouping (LPG). This method provides better preservation of image local structures. In this method a pixel and its nearest neighbors are modeled as a vector variable whose training samples are selected from the local window by using block matching based LPG. In image de-noising, a compromise has to be found between noise reduction and preserving significant image details. PCA is a statistical technique for simplifying a dataset by reducing datasets to lower dimensions. It is a standard technique commonly used for data reduction in statistical pattern recognition and signal processing. This paper proposes a de-noising technique by using a new statistical approach, principal component analysis with local pixel grouping (LPG). This procedure is iterated second time to further improve the de-noising performance, and the noise level is adaptively adjusted in the second stage.
Fpga implementation of fusion technique for fingerprint applicationIAEME Publication
Image Fusion is a process of combining relevant information from a set of images, into a
single image, wherein the resultant fused image will be more informative and complete than any of
the input images. This paper discusses Laplacian Pyramid (LP) based image fusion techniques for
fingerprint application. The technique is implemented in MatLab and evaluation parameters Mean
Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Matching score are discussed. As well
the same implemented on Virtex-5 FPGA development board using Verilog HDL. LP based
technique provides better results for image fusion than other techniques.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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 ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
Currently, in both market and the academic communities have required applications based on image and video processing with several real-time constraints. On the other hand, detection of moving objects is a very important task in mobile robotics and surveillance applications. In order to achieve this, we are using a alternative means for real time motion detection systems. This paper proposes hardware architecture for motion detection based on the background subtraction algorithm, which is implemented on FPGAs (Field Programmable Gate Arrays). For achieving this, the following steps are executed: (a) a background image (in gray-level format) is stored in an external SRAM memory, (b) a low-pass filter is applied to both the stored and current images, (c) a subtraction operation between both images is obtained, and (d) a morphological filter is applied over the resulting image. Afterward, the gravity center of the object is calculated and sent to a PC (via RS-232 interface).
HUMAN ACTION RECOGNITION IN VIDEOS USING STABLE FEATURES sipij
Human action recognition is still a challenging problem and researchers are focusing to investigate this
problem using different techniques. We propose a robust approach for human action recognition. This is
achieved by extracting stable spatio-temporal features in terms of pairwise local binary pattern (P-LBP)
and scale invariant feature transform (SIFT). These features are used to train an MLP neural network
during the training stage, and the action classes are inferred from the test videos during the testing stage.
The proposed features well match the motion of individuals and their consistency, and accuracy is higher
using a challenging dataset. The experimental evaluation is conducted on a benchmark dataset commonly
used for human action recognition. In addition, we show that our approach outperforms individual features
i.e. considering only spatial and only temporal feature.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Motion Detection and Clustering Using PCA and NN in Color Image SequenceTELKOMNIKA JOURNAL
This paper presents a motion detection method with the use of the Principal Component
Analysis. This method is able to detect and track moving objects in a sequence of images. The tested
sequence is segmented within the meaning of movement. In this paper, the concept of extracting
significant information from a large number of data is adopted to provide an effective method for tracking
moving objects on the video image. The principal components are different in term of getting significant
information, the nature of motion (the nature of information) is responsible of this difference, the algorithm
in this paper distinguish the motion nature and choose the appropriate components to give a best
segmentation.
Modified Adaptive Lifting Structure Of CDF 9/7 Wavelet With Spiht For Lossy I...idescitation
We present a modified structure of 2-D cdf 9/7 wavelet
transforms based on adaptive lifting in image coding. Instead
of alternately applying horizontal and vertical lifting, as in
present practice, Adaptive lifting performs lifting-based
prediction in local windows in the direction of high pixel
correlation. Hence, it adapts far better to the image orientation
features in local windows. The predicting and updating signals
of Adaptive lifting can be derived even at the fractional pixel
precision level to achieve high resolution, while still
maintaining perfect reconstruction. To enhance the
performance of adaptive based modified structure of 2-D CDF
9/7 is coupled with SPIHT coding algorithm to improve the
drawbacks of wavelet transform. Experimental results show
that the proposed modified scheme based image coding
technique outperforms JPEG 2000 in both PSNR and visual
quality, with the improvement up to 6.0 dB than existing
structure on images with rich orientation features .
Introduction to Wavelet Transform and Two Stage Image DE noising Using Princi...ijsrd.com
In past two decades there are various techniques are developed to support variety of image processing applications. The applications of image processing include medical, satellite, space, transmission and storage, radar and sonar etc. But noise in image effect all applications. So it is necessary to remove noise from image. There are various methods and techniques are there to remove noise from images. Wavelet transform (WT) has been proved to be effective in noise removal but this have some problems that is overcome by PCA method. This paper presents an efficient image de-noising scheme by using principal component analysis (PCA) with local pixel grouping (LPG). This method provides better preservation of image local structures. In this method a pixel and its nearest neighbors are modeled as a vector variable whose training samples are selected from the local window by using block matching based LPG. In image de-noising, a compromise has to be found between noise reduction and preserving significant image details. PCA is a statistical technique for simplifying a dataset by reducing datasets to lower dimensions. It is a standard technique commonly used for data reduction in statistical pattern recognition and signal processing. This paper proposes a de-noising technique by using a new statistical approach, principal component analysis with local pixel grouping (LPG). This procedure is iterated second time to further improve the de-noising performance, and the noise level is adaptively adjusted in the second stage.
Fpga implementation of fusion technique for fingerprint applicationIAEME Publication
Image Fusion is a process of combining relevant information from a set of images, into a
single image, wherein the resultant fused image will be more informative and complete than any of
the input images. This paper discusses Laplacian Pyramid (LP) based image fusion techniques for
fingerprint application. The technique is implemented in MatLab and evaluation parameters Mean
Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Matching score are discussed. As well
the same implemented on Virtex-5 FPGA development board using Verilog HDL. LP based
technique provides better results for image fusion than other techniques.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Automatic identification of animal using visual and motion saliencyeSAT Publishing House
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
Efficient 3D stereo vision stabilization for multi-camera viewpointsjournalBEEI
In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing
the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method.
Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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.
Real-time Moving Object Detection using SURFiosrjce
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.
Fast Motion Estimation for Quad-Tree Based Video Coder Using Normalized Cross...CSCJournals
Motion estimation is the most challenging and time consuming stage in block based video codec. To reduce the computation time, many fast motion estimation algorithms were proposed and implemented. This paper proposes a quad-tree based Normalized Cross Correlation (NCC) measure for obtaining estimates of inter-frame motion. The measure operates in frequency domain using FFT algorithm as the similarity measure with an exhaustive full search in region of interest. NCC is a more suitable similarity measure than Sum of Absolute Difference (SAD) for reducing the temporal redundancy in video compression since we can attain flatter residual after motion compensation. The degrees of homogeneous and stationery regions are determined by selecting suitable initial fixed threshold for block partitioning. An experimental result of the proposed method shows that actual numbers of motion vectors are significantly less compared to existing methods with marginal effect on the quality of reconstructed frame. It also gives higher speed up ratio for both fixed block and quad-tree based motion estimation methods.
Repeat-Frame Selection Algorithm for Frame Rate Video TranscodingCSCJournals
To realize frame rate transcoding, the forward frame repeat mechanism is usually adopted to compensate the skipped frames in the video decoder for end-user. However, based on our observation, it is unsuitable for repeating all skipped frames only in the forward direction and sometimes the backward repeat may achieve better results. To deal with this issue, we propose the new reference frame selection method to determine the direction of repeat-frame for skipped Predictive (P) and Bidirectional (B) frames. For P-frame, the non-zero transformed coefficients and the magnitude of motion vectors are taken into consideration to determine the use of forward or backward repeat. For B-frame, the magnitude of motion vector and its corresponding reference directions of the blocks in B-frame are selected to be the decision criteria. Experimental results show that the proposed method provides 1.34 dB and 1.31 dB PSNR improvements in average for P and B frames, respectively, compared with forward frame repeat.
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.
High Speed and Area Efficient 2D DWT Processor Based Image Compressionsipij
This paper presents a high speed and area efficient DWT processor based design for Image Compression applications. In this proposed design, pipelined partially serial architecture has been used to enhance the speed along with optimal utilization and resources available on target FPGA. The proposed model has been designed and simulated using Simulink and System Generator blocks, synthesized with Xilinx Synthesis tool (XST) and implemented on Spartan 2 and 3 based XC2S100-5tq144 and XC3S500E-4fg320 target device. The results show that proposed design can operate at maximum frequency 231 MHz in case of Spartan 3 by consuming power of 117mW at 28 degree/c junction temperature. The result comparison has shown an improvement of 15% in speed.
Similar to ADAPTIVE, SCALABLE, TRANSFORMDOMAIN GLOBAL MOTION ESTIMATION FOR VIDEO STABILIZATION (20)
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
Using social media in education provides learners with an informal way for communication. Informal communication tends to remove barriers and hence promotes student engagement. This paper presents our experience in using three different social media technologies in teaching software project management course. We conducted different surveys at the end of every semester to evaluate students’ satisfaction and engagement. Results show that using social media enhances students’ engagement and satisfaction. However, familiarity with the tool is an important factor for student satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The amount of piracy in the streaming digital content in general and the music industry in specific is posing a real challenge to digital content owners. This paper presents a DRM solution to monetizing, tracking and controlling online streaming content cross platforms for IP enabled devices. The paper benefits from the current advances in Blockchain and cryptocurrencies. Specifically, the paper presents a Global Music Asset Assurance (GoMAA) digital currency and presents the iMediaStreams Blockchain to enable the secure dissemination and tracking of the streamed content. The proposed solution provides the data owner the ability to control the flow of information even after it has been released by creating a secure, selfinstalled, cross platform reader located on the digital content file header. The proposed system provides the content owners’ options to manage their digital information (audio, video, speech, etc.), including the tracking of the most consumed segments, once it is release. The system benefits from token distribution between the content owner (Music Bands), the content distributer (Online Radio Stations) and the content consumer(Fans) on the system blockchain.
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This paper discusses the importance of verb suffix mapping in Discourse translation system. In
discourse translation, the crucial step is Anaphora resolution and generation. In Anaphora
resolution, cohesion links like pronouns are identified between portions of text. These binders
make the text cohesive by referring to nouns appearing in the previous sentences or nouns
appearing in sentences after them. In Machine Translation systems, to convert the source
language sentences into meaningful target language sentences the verb suffixes should be
changed as per the cohesion links identified. This step of translation process is emphasized in
the present paper. Specifically, the discussion is on how the verbs change according to the
subjects and anaphors. To explain the concept, English is used as the source language (SL) and
an Indian language Telugu is used as Target language (TL)
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The using of information technology resources is rapidly increasing in organizations,
businesses, and even governments, that led to arise various attacks, and vulnerabilities in the
field. All resources make it a must to do frequently a penetration test (PT) for the environment
and see what can the attacker gain and what is the current environment's vulnerabilities. This
paper reviews some of the automated penetration testing techniques and presents its
enhancement over the traditional manual approaches. To the best of our knowledge, it is the
first research that takes into consideration the concept of penetration testing and the standards
in the area.This research tackles the comparison between the manual and automated
penetration testing, the main tools used in penetration testing. Additionally, compares between
some methodologies used to build an automated penetration testing platform.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
In order to treat and analyze real datasets, fuzzy association rules have been proposed. Several
algorithms have been introduced to extract these rules. However, these algorithms suffer from
the problems of utility, redundancy and large number of extracted fuzzy association rules. The
expert will then be confronted with this huge amount of fuzzy association rules. The task of
validation becomes fastidious. In order to solve these problems, we propose a new validation
method. Our method is based on three steps. (i) We extract a generic base of non redundant
fuzzy association rules by applying EFAR-PN algorithm based on fuzzy formal concept analysis.
(ii) we categorize extracted rules into groups and (iii) we evaluate the relevance of these rules
using structural equation model.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
2. 442 Computer Science & Information Technology (CS & IT)
Video stabilization is typically done through Global Motion Estimation (GME) and
Compensation. GME can be done in image domain using multiple techniques such as Flow-based
(e.g. Lucas-Kanade [6]) or Feature-based (e.g. SIFT, or matching best motion pairs across
frames). These either require elaborate multi-scale iterative computation over dense vector fields
in image domain [8] to overcome problems (such as small-motion assumption) or feature
clustering with RANSAC like methods (to overcome noise and brightness constancy
assumptions). GME can also be done in Transform domain using the well-known Phase
Correlation which was originally defined in 1970’s by Kuglin and Hines [4], which relates global
motion to phase shift in the spectrum which can be mapped back to a motion estimate derived as
the position of the peak in the correlation surface derived through an inverse transform of the
cross power spectrum of the two frames being compared.
Image domain methods are slower (except in feature/corner-rich images where feature based
methods perform faster), but they can do global as well as local motion estimation. Transform
domain methods are generally faster and more accurate on homogeneous images, and are resilient
to rapid illumination changes and large motion. Both these approaches can become very time
consuming if one needs more accuracy and smoothness. Scalable, non-adaptive approaches based
on image decomposition (say wavelet based) at a single scale of the image are known as well
(McGuire [2]) but these also sacrifice accuracy for speed.
We show here that wavelet transforms can be used to achieve significant speedup in this Fourier
domain computation without sacrificing accuracy, by focusing on specific sub-bands (adaptively
selected) and using the wavelet interpolation capability. Our approach yields a smooth, scalable,
and fast algorithm where two consecutive scale levels in a decomposition are adaptively chosen
(based on time requirement and past motion history) and adaptively combined in a novel way to
yield significantly better accuracy than a single level.
Image-domain global motion stabilization techniques typically require computation of dense
vector fields in a single resolution or of motion computation and combination across multiple
resolutions. Our approach does not involve dense computation, but instead it computes as usual
one FFT and one IFFT for the two selected levels to arrive at the final results. Our novel
adaptivity comes from averaging the motion or jitter over a running window and selecting the
sub-band pair where time complexity is least possible for this average. Also we note that ours is
not block search based (being in transform domain), but searches in scale space for the correct
pair of decomposition levels, and in the process introduces a novel multi-scale combination
approach to transform domain, which is well-known in the image domain as Lucas Kanade
pyramidal iterative tracker [8].
Note that a 2D global motion estimate is sufficient to do the video stabilization which we are
interested in, and that we are not interested in local motion or object tracking or 3D stabilization.
Note also that, in our paper here, our objective is to compare our novel multi-scale phase
correlation against the usual single level phase correlation in terms of speed and accuracy (we
achieve 15 msec per frame on 320 X 240 30 fps video on a common laptop, 30% faster than
normal phase correlation for similar accuracy). Our goal is real time stabilization of video with
time to spare for additional tasks, it is not to compare against RANSAC based feature driven
methods which are slower at 70 msec per frame on same video with a GPU on same laptop.
3. Computer Science & Information Technology (CS & IT) 443
2. TRANSLATION USING THE TRANSFORM DOMAIN METHOD
Phase correlation is a well-known, illumination-invariant fast, transform domain method for
global motion estimation [1], [2], [3], [4]. It utilizes the phase of Fourier transform coefficients to
estimate motion down to a sub-pixel level. Motion can be estimated independently in either axis
(however, translational motion has to be less than or equal to half the image size in either
direction). The algorithm is described below. Let Fi and Fi+1 be the frames under consideration,
where Fi is the anchor frame, with respect to which, the global translation of Fi+1 is estimated
The shift values xo,yo are the co-ordinates of the maximum value of I. The co-ordinates xo,yo
give us the relative translation from frame k to frame k+1 Stabilization is effected by shifting the
second frame back by X, Y pixels. Further, for small angles of rotation, the rotation can be
approximated as a linear translation.
2.1 Adaptive Scalability Using Wavelets
In most cases, with a human operator, motion in either axis does not remain similar in magnitude
(for instance in a given situation the shake could be mostly be vertical. In such cases, repeated
computation of Fourier transform to the same extent on both axes becomes computationally
unnecessary. The above Fourier based approach can then be combined with the wavelet
transforms (we use Haar for computational simplicity) to provide a scalable version of phase
correlation [2]. Given that the motion is often not equal in both directions, the separable nature of
the wavelet transform can be used to perform the computation adaptively by asymmetrically
scaling the spatial image resolution across axes for better speed. Thus, it is possible to choose a
single sub band and perform the Fourier transform only on that sub band to obtain the translation
estimates as described above. Further, it is also possible to control the choice of sub-band
adaptively through the use of a cost function dependent on prior motion history. In the majority of
cases, with a human operator, the motion is not constant but usually converges to some steady
state. In such cases, we can use the motion obtained from previous frames to decide the sub-band
on which the motion estimates are computed for the next frame pair. Thus the scalability is
adaptively controlled from the previous motion history.
3. MOTION VECTOR SIMULATION
The motion vectors in x and y were modeled as a zero mean Gaussian random process of a
sequence of 40 frames. The variance in the motion vectors was used as a criterion of stabilization.
The results for 4 different random Gaussian motion sequences on the same sequence of 40 frames
4. 444 Computer Science & Information Technology (CS & IT)
are as shown below. The motion estimate was computed for the next frame as the mean of the
mean of the motion vectors of the previous 5 frames independently in x and y, a reduction in
motion is seen in the reduced variance of motion vectors
Table 1. The variance of motion in x and y learnt from queue of 5 frames before and after stabilization
Table 2. The variance of motion in x and y for different frame queue sizes averaged over 10 sequences for
the same queue size
Fig. 1. (a),(b),(c),(d), motion without compensation (blue), and with compensation (red) in horizontal (
above) and vertical( below) directions)
0 5 10 15 20 25 30 35 40
-20
0
20
40
motion in x axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-100
-50
0
50
motion in y axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-20
-10
0
10
20
motion in x axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-50
0
50
100
motion in y axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-40
-20
0
20
motion in x axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-50
0
50
motion in y axis
motioninpixels
0 5 10 15 20 25 30 35 40
-40
-20
0
20
40
motion in x axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-50
0
50
motion in y axis
frame no
motioninpixels
Motion
sequence
X Variance
(before stabilization)
Y Variance
(before stabilization)
X Variance
(after stabilization)
Y Variance
(after stabilization)
1 92.97 380.99 9.176 49.012
2 90.83 384.51 5.38 15.78
3 91.855 387.58 15.42 5.446
4 93.33 381.57 5.207 26.33
Frame
queue size
X Variance
(before stabilization)
Y Variance
(before stabilization )
X Variance
(after stabilization)
Y Variance
(after stabilization)
3 92.43 384.13 11.53 46.24
5 92.03 385.15 10.74 21.06
7 92.02 384.16 9.02 23.16
5. Computer Science & Information Technology (CS & IT) 445
Fig. 2. the sub band at the corresponding frame in x (red) and y(black) direction determined using the
motion estimates of previous 5 frames
0 5 10 15 20 25 30 35 40
1
1.5
2
2.5
3
3.5
4
frameNo
4. MOTION ESTIMATION USING INFORMATION FROM MULTIPLE
BANDS
Due to the decreasing scale information at higher bands, the errors in estimating the motion
increases as higher and smaller bands in the decomposition are used for stabilization. To achieve
the stabilization at a lower cost, while still keeping the stabilization quality, we use the
interpolation property of wavelets to refine this estimate by averaging from multiple bands.
Interpolation of a signal is, in essence, the up sampling of the signal followed by convolution with
the interpolation filter.
Taking inverse DWT of only the coefficients at a lower scale can be used to obtain a ‘low
resolution’ estimate of the image motion. Consequently, in obtaining the motion estimate, the
peak of the phase correlation follows a similar pattern in obtaining motion estimates in the ‘scale
space’, as is seen in image coding algorithms such as SPIHT [7].With the use of the Haar
wavelet, this interpolation reduces to the simple nearest neighbor case and the pixels duplicate in
the direction of the transform.
Performing phase correlation of the entire image gives us an exact location of the motion vector.
Using phase correlation on the one-level decomposition of the vector allows localization to an
area of 2 pixels x 2 pixels, where the exact motion vector may be located and hence the error,
increases exponentially as the size of the band reduces. This increase is countered by a weighted
average of the motion vectors from multiple bands.
Let X, Y be the original motion estimates. Let X1 Y1 be the motion estimates from the phase
correlation 1 level decomposition
Using wavelet interpolation property of the Haar wavelet
X1’=2*X1 +0.5*sgn(X1) 4.1
Y1’=2*Y1 +0.5*sgn(Y1) 4.2
Let X2 Y2 be the motion estimates from the 2 level decomposition
X2’=4*X2 +1*sgn(X2) 4.3
Y2’=4*Y2 +1*sgn(Y2) 4.4
6. 446 Computer Science & Information Technology (CS & IT)
The resultant motion estimate Xr, Yr
Xr= (aX1’+bX2’) 4.5
Yr= (aY1’+bY2’) 4.6
Further results using the described method to stabilize videos can be seen at this URL
“http://www.youtube.com/channel/UCyWEttTY774WqNy71fuCbFQ?feature=mhee”Videos with
unstab in their name are not stabilized. The videos with stab in their name have been stabilized by the
method described.
Fig. 3. (TOP) original motion vector (blue) stabilized with estimate from 1 band (red) and estimate from
multiple bands( green) in horizontal direction ( above ) and vertical direction ( below) (BOTTOM)
stabilization with unscaled phase
0 5 10 15 20 25 30 35 40
-40
-20
0
20
40
motion in x axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-20
0
20
40
motion in y axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-20
0
20
40
motion in x axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-40
-20
0
20
40
motion in y axis
frame no
motioninpixels
0 5 10 15 20 25 30 35 40
-20
0
20
40
frame no
ymotioninpixels
0 5 10 15 20 25 30 35 40
-40
-20
0
20
frame no
ymotioninpixels
0 5 10 15 20 25 30 35 40
-40
-20
0
20
frame no
ymotioninpixels
0 5 10 15 20 25 30 35 40
-40
-20
0
20
frame no
ymotioninpixels
5. COMPLEXITY ANALYSIS
It is important to note that the computational complexity with regards to our Fourier computation
needs would never reach the computation of the full Fourier transform, in spite of application to
multiple sub bands. Considering an NXN image, the complexity of the Fourier transform for one
frame is O (N2
log2N) For a 1 level decomposition of the wavelet sub band the Fourier time
domain complexity is reduced to O ((N/2)2
log2 (N/2)).
Refining the motion with estimates from sub bands of higher level decomposition and still lower
resolution (say second level of decomposition, with equal scaling in both x and y directions, The
total complexity of the Fourier transforms becomes
7. Computer Science & Information Technology (CS & IT) 447
Thus, in the limiting case, the complexity of performing the 2D Fourier transform is reduced to a
fraction of the original number of operations. Further, using the separable nature
of the wavelet transform the decomposition may be performed asymmetrically at a given sub
band, in this case, the complexity of the Fourier transform is O (N/2i
)(N/2j
)log2(N/2j
). In the
multi-sub band case with asymmetric scaling, the total cost is now
which reduces to
where i and j are sub band decomposition levels in x and y directions respectively and typically,
i,j <=k (see 5.2), as motion in one direction need not rely on information from motion in another
direction.
Due to the inherent low pass nature of the wavelet scaling function and repeated scaling
there is a loss of detail at each sub band level. This will inevitably reduce the amount of available
frequency information available in the sub bands as the number of sub bands increase till the
point where the frequency information in a given sub band does not have any change in phase
from frame to frame thus placing a lower bound on the number of sub bands to be considered.
The table below shows a comparison of our proposed method against existing phase correlation
method for 3 sets of 10 random Gaussian motion sequences, each of length 40 frames on frames
of resolution 256x256.The variance and time taken were averaged over the 10 sequences in each
set. The mean baseline variance of the 3 motion sequences was 93.23 in x and 94.15 in y
direction. The simulations were performed in MATLAB on a HP 8640 laptop with i5 processor
Table 3. Comparison of motion in X and Y with time taken against PC method.
Motion
sequence
set
Normal phase correlation
(variance in X, Y, and Time
taken)
Proposed method
(variance in X, Y, and Time taken)
1 7.16 7.14 0.8725s 5.70 5.55 0.5855s
2 6.92 8.80 0.8715s 4.18 5.67 0.615s
3 8.21 8.85 0.8728s 4.69 5.704 0.608s
8. 448 Computer Science & Information Technology (CS & IT)
Fig. 4. Pipeline of motion adaptive scalable stabilization system
6. CONCLUSIONS
Dense image-domain global stabilization methods like Lucas-Kanade (including optic flow) are
very expensive in terms of time, taking O(N3
) time and are affected by variation in illumination.
Transform domain global approaches such as phase correlation are illumination invariant and are
computationally cheaper but can become computationally intense at large image sizes due to
expensive large resolution. We have shown here that wavelet transforms can be used to achieve
significant speedup in this Fourier domain computation without sacrificing much accuracy, by
focusing on specific sub-bands and using wavelet interpolation capability utilized in image
coding algorithms such as SPIHT. Our approach yields an equally accurate scalable, motion-
adaptive, transform domain global stabilization algorithm at a lower computational complexity as
determined by the recent motion history.
ACKNOWLEDGMENTS
The authors thank Dr. Krishnamoorthy Palanisamy and Mandar Kulkarni of Philips Research
Bangalore for their helpful suggestions and comments and also Prof. V. M. Gadre of IIT Bombay
for his support.
REFERENCES
[1] B. Srinivasa Reddy and B. N. Chatterji,,”An FFT-Based Technique for Translation, Rotation, and
Scale-Invariant Image Registration” IEEE transactions on image processing, vol. 5 , no. 8, august
1996
[2] Morgan McGuire “An image registration technique for recovering rotation, scale and translation
parameters” MIT 1998
[3] H. S. Stone, M. T. Orchard, E.-C, Lucas, B. and Kanade, T. Chang, and S. A. Martucci, “A Fast
Direct Fourier-based Algorithm for Subpixel Registration of Image,” IEEE Transactions on
Geoscience and Remote Sensing, vol. 39, no. 10, pp. 2235–2243, 2001
9. Computer Science & Information Technology (CS & IT) 449
[4] Kuglin, C. D. and Hines, D. C., “The phase correlation image alignment method.” Proceedings of
IEEE International Conference on Cybernetics and Society, 1975. pp. 163-165, New York, NY, USA
[5] J. Shi and C. Tomasi "Good Features to Track.” , in Proc. IEEE Conf. onComputer Vision and Pattern
Recognition, pp. 593-600,1994
[6] B. Lucas, T.Kanade “An iterative image registration technique with an application to stereo vision”.
Proceedings of the International Joint Conference on Artificial Intelligence, pp. 674–679. 1981
[7] Amir Said, William Pearlman” A new and fast image codec based on set partitioning in hierarchical
trees”, IEEE transactions on circuits and systems in video technology
[8] J. Bouguet, “Pyramidal Implementation of the Lucas Kanade Feature Tracker: Description of the
Algorithm,” OpenCV Document, Intel Microprocessor Research Labs, 2000
[9] Y. Matsushita, E. Ofek, W.Ge,X. Tang, and H.-Y. Shum. “ Full frame video stabilization with motion
inpainting,” IEEE Transactions on Pattern Analysis and Machine Intelligence 1163, July 2006
[10] R. Szeliski, “Image Alignment and Stitching: A Tutorial,” Technical Report MSR-TR-2004-92,
Microsoft Corp., 2004
[11] A. Jain, Fundamentals of Digital Image Processing. Prentice-Hall, 1986, p. 321
[12] C. Morimoto and R. Chellappa, “Evaluation of image stabilization algorithms,” in Acoustics, Speech
and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on, vol. 5, may
1998, pp. 2789 –2792 vol.5.
[13] S. Baker and I. Matthews, “Lucas-Kanade 20 years on a unifying framework,” in Int’l Journal of
Computer Vision, vol. 56, no. 3, 2004, pp. 221-255.