Showing 1-25 of 6,278 resultsfor "Index Terms":Cross-correlation Algorithm
"Index Terms":Cross-correlation Algorithm
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A neural network learning for adaptively extracting cross-correlation features between two high-dimensional data streams
This paper proposes a novel cross-correlation neural network (CNN) model for finding the principal singular subspace of a cross-correlation matrix between two high-dimensional data streams. We introduce a novel nonquadratic criterion (NQC) for searching the optimum weights of two linear neural networks (LNN). The NQC exhibits a single global minimum attained if and only if the weight matrices of t...Show More
Performance Analysis of Isolated Speech Recognition Technique Using MFCC and Cross-Correlation
Md. Ekhlasur Rahaman;S. M. Shamsul Alam;Himadri Shekhar Mondal;Ahmed Saif Muntaseer;Rajib Mandal;M. Raihan
2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
Year: 2019 | Conference Paper |
Cited by: Papers (8)
Speech signal processing has become an important mode of interaction with computer. In this paper, Mel Frequency Cepstral Coefficient (MFCC) technique has been used to process speech samples to attain the recognition. MFCC is a term which narrate the short-term power spectrum of a speech signal, depend on a linear cosine transform (FFT and DCT we have used in our work) of a log power spectrum on a...Show More
Application of Cross-Correlation Algorithm in Radio Weak Signal Detection
2009 Seventh Annual Communication Networks and Services Research Conference
Year: 2009 | Conference Paper |
Cited by: Papers (5)
Signal detection in low signal to noise ratio (SNR) is widely concerned. In this paper, an algorithm for weak signals detection based on Cross-correlation analysis is proposed. The simulation results show that this algorithm is a fairly effective method for improving the ratios of signal to noise. Using this algorithm in radio monitoring, we can raise the sensitivity of the monitoring system and e...Show More
Comparison of the Neural Networks with Crosscorrelation Algorithm for the Displacements on Images Estimation
V. V. Pinchukov;A. Yu. Poroykov;E. V. Shmatko;A. D. Bogachev;N. Yu. Sivov
2022 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)
Year: 2022 | Conference Paper |
In this paper three methods for determining displacements on images are compared. Two of them are neural networks designed for Particle Image Velocimetry images processing. The third method is classic cross-correlation approach. For estimation the accuracy of the algorithms synthetic data were used. Based on the obtained simulation results, it can be concluded that the use of neural networks is pr...Show More
Fast Template Matching Based on Normalized Cross Correlation with Centroid Bounding
2010 International Conference on Measuring Technology and Mechatronics Automation
Year: 2010 | Conference Paper |
Cited by: Papers (16)
In this paper, we propose a fast pattern matching algorithm based on normalized cross correlation (NCC) with centroid bounding to achieve very efficient search. The algorithm will calculate histogram around centroid within maximum circle with radius R. After dividing the image into blocks by R×R size, calculating the similarity between the color histograms of the image block and centroid around ci...Show More
Fast Template Matching Based on Normalized Cross Correlation With Adaptive Multilevel Winner Update
In this paper, we propose a fast pattern matching algorithm based on the normalized cross correlation (NCC) criterion by combining adaptive multilevel partition with the winner update scheme to achieve very efficient search. This winner update scheme is applied in conjunction with an upper bound for the cross correlation derived from Cauchy-Schwarz inequality. To apply the winner update scheme in ...Show More
A modified Normalized Cross-Correlation algorithm for Embedded Systems
Ismael Lopez Sanchez;Miguel Angel Rosas Galaviz;Damian Gomez Herrera;Luis Rizo Dominguez
2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
Year: 2021 | Conference Paper |
Problems related to image matching, such as processing time, performance, and changes in rotation and scale are widely studied. However, creating simple solutions for image matching that can be implemented in an embedded system has been overlooked. Therefore, this paper proposes a modified Normalized Cross-Correlation algorithm for embedded systems aimed at creating a low-cost solution for a cemen...Show More
An efficient implementation of normalized cross-correlation image matching based on pyramid
2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)
Year: 2013 | Conference Paper |
Cited by: Papers (6)
Normalized Cross-Correlation (NCC) image matching algorithm based on gray correlation provides accurate results however it consumes a significant time for large amount of calculations. The main contribution of this paper is implementing the NCC image matching algorithm in parallel. Moreover, it proposes and implements the NCCP based on pyramid to reduce the time.Show More
Coupled cross-correlation neural network algorithm for principal singular triplet extraction of a cross-covariance matrix
This paper proposes a novel coupled neural network learning algorithm to extract the principal singular triplet (PST) of a cross-correlation matrix between two high-dimensional data streams. We firstly introduce a novel information criterion (NIC), in which the stationary points are singular triplet of the crosscorrelation matrix. Then, based on Newton's method, we obtain a coupled system of ordin...Show More
Improved 2-D DOA estimation algorithm for L-shaped array using cross-correlation matrix
7th IET International Conference on Wireless, Mobile & Multimedia Networks (ICWMMN 2017)
Year: 2017 | Conference Paper |
This letter presents an improved two-dimensional (2-D) direction-of-arrival (DOA) estimation algorithm for L-shaped array. Based on the relationship among three partitions of the steering vectors, the 2-D DOAs are estimated. By multiplying a selection matrix, the estimation error in Nizar's algorithm is compensated. The proposed algorithm can achieve good estimation performance when the elevation ...Show More
A genetic-optimized multi-angle normalized cross correlation SIFT for automatic remote sensing registration
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Year: 2016 | Conference Paper |
Cited by: Papers (6)
A new method of remote sensing image registration is proposed to reduce the adverse effects on the image registration caused by the rotation transform, based on genetic-optimized multi-angle normalized cross correlation (GMNCC) to get more matched scale invariant feature transform (SIFT) feature points. The GMNCC can detect the angle-offsets (AOs) of object images to reference image by determining...Show More
Iterative Reweighted Local Cross Correlation Method for Nonlinear Registration of Multiphase Liver CT Images
2021 IEEE International Conference on Image Processing (ICIP)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
It is of great importance for proper radiological interpretations to register multiphase liver scans, but much challenging due to different breathing-holding levels and physiological motions while imaging. In this paper, we propose a novel nonlinear registration method for multiphase liver scans upon iterative reweighted local cross correlation (IRLCC) measure, which employs the metric of local cr...Show More
Heartbeat Estimation and Respiratory Arrhythmia Detection Using 24 GHz Radar Signals
Michelle R. Tchameni;Volker Lücken;Udo Schroeder;Andreas R. Diewald
2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)
Year: 2024 | Conference Paper |
In this paper, we propose a novel non-contact method for monitoring vital signs, with a focus on heartbeat estimation using radar signals. Our approach utilizes a cross-correlation method based on a template function to isolate cardiac information from phase-extracted radar signals recorded during breathing. By accurately identifying heartbeat peaks over time, our method demonstrates the potential...Show More
Performance Evaluation of Unsupervised Coregistration Algorithms for Multitemporal SAR Images
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Year: 2022 | Conference Paper |
In this paper, we present three algorithms for the multitemporal synthetic aperture radar (SAR) images coregistration. The proposed algorithms are a 2-D cross correlation, a 1-D parabolic based, and a 2-D projective transformation. The 2-D cross correlation algorithm is used to obtain coarse estimation of the displacement for coregistration. In the second method, two independent 1-D parabolic inte...Show More
A Proposed Template Image Matching Algorithm for Face Recognition
2019 IEEE 7th Palestinian International Conference on Electrical and Computer Engineering (PICECE)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
Automatic matching of people faces is a demanding issue which has recently received increased attention during the recent ages due to its various uses in different applications such as law implementation, security requirements and video indexing. Face images are exposed to a variety of important influences such as illumination variation, difference in looking view, facial expression, occlusion, ag...Show More
Moving object detection in dynamic background
Proceedings of the 33rd Chinese Control Conference
Year: 2014 | Conference Paper |
Cited by: Papers (2)
A new method of detecting moving object in dynamic background is proposed in this paper. At first, an adaptive threshold Harris algorithm is proposed in this paper to extract feature points, then, SIFT algorithm is used to describe these extracted feature points. The similarity function is used to match feature points and RANSAC algorithm is used to eliminate the pseudo matches. According to the c...Show More
The adaptive hybrid algorithm for sea clutter denoising based on CEEMDAN
2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)
Year: 2017 | Conference Paper |
Cited by: Papers (1)
Based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) theory, a new adaptive hybrid algorithm for sea clutter denoising is proposed. The chaotic sea clutter signals are decomposed into several intrinsic modal functions (IMF) which start from high-frequency scales to low-frequency scales by using CEEMDAN. According to the relationship between the pretreatment thr...Show More
Adaptive algorithms for double-talk echo cancelling
Ioana Homana;Marina Topa;Botond Sandor Kirei;Cristian Contan
2010 9th International Symposium on Electronics and Telecommunications
Year: 2010 | Conference Paper |
Cited by: Papers (2)
In the paper, an echo canceller based on a system identification scheme with adaptive algorithms is presented. The algorithms consider FIR filters with the taps chosen to minimize an error signal derived from the system according to a stochastic gradient-based method. The following adaptive filters are discussed and simulated in Matlab: classical LMS and its variants: NLMS, VSLMS, VSNLMS and RLS. ...Show More
A faster image registration algorithm
2010 3rd International Congress on Image and Signal Processing
Year: 2010 | Conference Paper |
Cited by: Papers (3)
Image registration is of prime importance for image mosaic. It is the process of geometrically aligning one image to another image of the same scene taken from different time, from different viewpoints or by different sensors. In general, image registration needs a lot of time. This paper reduces the computation time from two aspects. For coarse matching, the paper combines normalized cross correl...Show More
Research on Multi-sensor Fusion Algorithm Based on Improved DS Evidence Theory
2023 15th International Conference on Communication Software and Networks (ICCSN)
Year: 2023 | Conference Paper |
The traditional airport runway foreign object automatic detection system has a single monitoring method for foreign objects, and the multi technology system monitoring method is the future development trend. However, when multiple technology systems monitor, the fusion algorithm is prone to evidence conflict and failure. This article proposes a multi-sensor fusion algorithm based on the improved D...Show More
An Efficient and Robust Self-Calibration Algorithm for Translation Position Errors in Ptychography
Li Liu;Lei Zhong;Ming Gong;Jinxiang Du;Honggang Gu;Shiyuan Liu
Ptychography, one kind of the large-field-of-view and high-resolution computational imaging, is consistently hampered by the motion errors of linear translation stages, i.e., the resolution of lensless ptychographic microscope cannot break through the positioning accuracy of its translation stages. Here, an accurate, fast, and robust self-calibration algorithm is proposed to refine the translation...Show More
Image processing by means of some bio-inspired optimization algorithms
Silviu-Ioan Bejinariu;Hariton Costin;Florin Rotaru;Ramona Luca;Cristina Niţă
2015 E-Health and Bioengineering Conference (EHB)
Year: 2015 | Conference Paper |
Cited by: Papers (6)
Image processing problems often require optimization algorithms to be applied. In this paper some aspects concerning the behavior of Bat and Cuckoo Search optimization algorithms are presented. The obtained accuracy and the processing time depend on the input images characteristics, chosen optimization criteria, dimension of the search space and, last but not least, on the chosen optimization algo...Show More
A Region-Based Normalized Cross Correlation Algorithm for the Vision-Based Positioning of Elongated IC Chips
With the development of integrated circuit (IC) chips, many elongated chips with small amounts of textures have begun to be used in IC packaging and manufacturing. Traditional template-matching methods are not effective for positioning these chips; this limitation results in IC equipment that cannot accurately pick up an elongated IC chip or may package a nonworking IC chip onto an electronic devi...Show More
Real-Time Hyperbola Recognition and Fitting in GPR Data
The problem of automatically recognizing and fitting hyperbolae from ground-penetrating radar (GPR) images is addressed, and a novel technique computationally suitable for real-time on-site application is proposed. After preprocessing of the input GPR images, a novel thresholding method is applied to separate the regions of interest from background. A novel column-connection clustering (C3) algori...Show More
Research on Multiple Cross Correlation Fusion Method of Fault Vibration Signal
2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Auto-correlation and cross-correlation methods are combined with other signal processing methods, which are widely used in identifying fault sources and extracting fault features, but the extracted fault features are not obvious enough. Compared with the auto-correlation and cross-correlation methods in signal processing, this paper proposes a vibration signal multi-cross correlation fusion algori...Show More
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