Query: Binary sequence matching system

Candidate papers:

abstract: Abstract. Photonic firewalls that can directly conduct the data discrimination and intrusion detection at the optical layer are an important security technique for optical networks. In the photonic firewall, binary sequence matching module is the core part and is implemented by multiple all optical logic gates such as all optical AND gate, all optical XOR gate, etc. However, the semiconductor optical amplifier (SOA) based all optical logic gates have the disadvantages of low operation rate which leads to low matching rate. We design a binary sequence matching module that is implemented by the cross phase modulation effect (XPM) and the four wave mixing effect (FWM) of the highly nonlinear fiber (HNLF) The nonlinear effect of HNLF has a very short response time, thus it can realize the logic operation at a very high optical signal rate. The developed binary sequence matching module is verified through VPI Transmission Maker 8.5. The simulation results show that it can achieve the matching of 8 bit data in 64 bit binary data at 160 Gbps signal rate.
author_names: Yu Liu

Xin Li

Ying Tang

Zicheng Shi

Shanguo Huang
title: Binary sequence matching system based on cross phase modulation and four wave mixing in highly nonlinear fibers
year: 2020

abstract: Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS) However, visual based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is related to the strong appearance changes that occur in scenes due to weather or season changes. In this paper, a place recognition based visual localization method is proposed, which realizes the localization by identifying previously visited places using the sequence matching method. It operates by matching query image sequences to an image database acquired previously (video acquired during traveling period) In this method, in order to improve matching accuracy, multi feature is constructed by combining a global GIST descriptor and local binary feature CSLBP (Center symmetric local binary patterns) to represent image sequence. Then, similarity measurement according to Chi square distance is used for effective sequences matching. For experimental evaluation, the relationship between image sequence length and sequences matching performance is studied. To show its effectiveness, the proposed method is tested and evaluated in four seasons outdoor environments. The results have shown improved precision recall performance against the state of the art SeqSLAM algorithm.
author_names: Yongliang Qiao

Cindy Cappelle

Yassine Ruichek
title: Visual Localization across Seasons Using Sequence Matching Based on Multi Feature Combination
venue: Sensors
year: 2017

abstract: Sonar system has a bell shaped magnitude spectrum. The spectrum matching degree of excitation sequence with that of sonar system is important to increase echo energy, which is related closely with the measurement range. Binary excitation sequences modulated using chaotic series, including chaotic binary amplitude shift keying, chaotic binary frequency shift keying and chaotic binary phase shift keying, are proposed in this paper. The spectrum matching degree of the proposed excitation sequences with that of sonar system is analyzed. Sonar experiments applying SensComp 600 series instrument grade electrostatic sensors excited with chaotic binary modulation sequences validate the analytical results.
author_names: Zhenjing Yao

YanXing Song

Jingsong Yang

Qin Gao
title: Spectrum matching analysis of chaotic binary modulation excitation sequence for sonar systems
venue: 2012 IEEE 11th International Conference on Signal Processing
year: 2012

abstract: We propose an all optical logic gate based binary sequence matching system for OOK modulated format optical signals at high information rate by using cross phase modulation (XPM) and four wave mixing (FWM) in high nonlinear fiber (HNLF) Through the simulation successfully demonstrates that the system can identify and locate the known 8bit detection sequence from the input 64bit target sequence at the information rate of 80Gbps.
author_names: Yu Liu

Shanguo Huang

Xin Li
title: Photonic Firewall Oriented Fast All Optical Binary Pattern Recognition
venue: 2020 International Conference on Optical Network Design and Modeling (ONDM)
year: 2020

abstract: In order to solve the problems of low precision,dependence and low mobility for common vehicle velocity measurement system,a vehicle borne autonomous velocity measurement model is designed.Therefore,the problem of vehicle velocity measurement is transformed into sequence image matching.Considering the constrained parameters of vehicle movement and the characteristics of sequence images,sequence image matching method is analyzed in four aspects of feature extraction,similarity measurement,searching space and searching strategy.Image matching algorithm is also designed.The simulation result shows that the matching method base on binary images and similarity measurement of mean absolute error function ensure computation complexity greatly reduced with a high computation efficiency.And the proposed matching algorithm exhibits a behavior with a high matching precision and speed.The result of vehicular test proves the effectiveness and reliability of the proposed method.
author_names: Liu Hong-lian
title: Research on vehicle borne autonomous velocity measurement method based on sequence image matching
year: 2015

abstract: Traffic monitoring through video processing is one of the hot research areas in the Intelligent Transportation System (ITS) Vehicle counting systems should be simple enough to be applied in real time circumstances. A novel and fast algorithm for vehicle counting from a traffic video sequence is proposed in this paper where the vehicle tracking step is not necessary. A reference model is only created in the video frames for a narrow area. When going through this narrow area, the moving vehicles are identified as foreground objects. Detection of moving vehicles is achieved by integrating approximated median filter based background subtraction with binary integral projection. The detected candidates are counted as a vehicle using a novel pixel matching search algorithm. The proposed algorithm does not rely on every video frame. It only requires every third frame for processing and thus increases the computation speed by three times compared to existing techniques. The proposed algorithm is tested and validated on a standard data set as well as a custom data set. Two parameters such as accuracy and processing time are used for the system evaluation where an overall accuracy of 96.84% is achieved. The processing time results show that the proposed system can perform in real time with an average real time processing speed of 93.92%
author_names: M HarikrishnanP

Anju Thomas

S NishaJ

Varun P Gopi

Ponnusamy Palanisamy
title: Pixel matching search algorithm for counting moving vehicle in highway traffic videos
venue: Multim. Tools Appl.
year: 2021

abstract: This work presents a K NN feature matching for monocular visual odometry (VO) system that can perform in realtime. By feeding a monocular video sequence, the proposed method continuously determines the instantaneous 6 DOF camera pose. After obtaining binary descriptors for image features, we adopt k nearest neighbor algorithm with Hamming distance calculation as a novel method for feature matching. Then, with our designed robust motion estimation, the system can operate in real time scenario for a large scale outdoor environment without utilizing GPU or reducing input image size. The experimental result shows a successfully built trajectory path without non linear optimization and loop closure for a challenging video sequences of KITTI dataset. Moreover, the comparison in terms of root mean square error with ORB SLAM and Semidirect Visual Odometry (SVO) are also presented.
author_names: Noppadol Pudchuen

Chirdpong Deelertpaiboon
title: Visual Odometry Based on K Nearest Neighbor Matching and Robust Motion Estimation
venue: 2018 International Electrical Engineering Congress (iEECON)
year: 2018

abstract: Using MESA code (Modules for Experiments in Stellar Astrophysics, version 9575) an evaluation was made of the evolutionary state of the epsilon Aurigae binary system (HD 31964, F0Iap disk) We sought to satisfy several observational constraints: 1) requiring evolutionary tracks to pass close to the current temperature and luminosity of the primary star; 2) obtaining a period near the observed value of 27.1 years; 3) matching a mass function of 3.0; 4) concurrent Roche lobe overflow and mass transfer; 5) an isotopic ratio 12 C/ 13 C 5 and, (6) matching the interferometrically determined angular diameter. A MESA model starting with binary masses of 9.85 4.5 Msun with a 100 day initial period, produces a 1.2 10.6 Msun result having a 547 day period, and a single digit 12 C/ 13 C ratio. These values were reached near an age of 20 Myr, when the donor star comes close to the observed luminosity and temperature for epsilon Aurigae A, as a post RGB/pre AGB star. Contemporaneously, the accretor then appears as an upper main sequence, early B type star. This benchmark model can provide a basis for further exploration of this interacting binary, and other long period binary stars.
author_names: Justus L Gibson

Robert E Stencel
title: MESA models of the evolutionary state of the interacting binary epsilon Aurigae
year: 2018

abstract: A Novel Linear Barcode scanning system based on a Dynamic template matching scheme. The proposed system works entirely in the Spatial domain and is capable of reading Linear Barcodes from low resolution Images containing severe OOF blur. This paper treats Linear barcode scanning under the perspective of deformed Binary waveform analysis and classification. A directed graphical model is designed to characterize the relationship between the blurred barcode waveform and its corresponding symbol value at any specific blur level. A Dynamic programming based inference algorithm is designed to retrieve the optimal state sequence, enabling real time
author_names: Enugula Niharika

Ismail Shurab
title: LINEAR BARCODE SCANNING SYSTEM BASED ON DYNAMIC TEMPLATE MATCHING FOR OOF BLURRED IMAGES
year: 2015

abstract: The emergence of autocatalytic structures in model chemistries has been a prominent subject throughout the history of artificial life research (Rasmussen (1985) Farmer et al. (1986) Kauffman (1986) Rasmussen (1989) Hordijk et al. (2011) and others) Most of these works have been concerned with the likelihood of finding autocatalytic sets in a population of random cross catalytic molecules. Here, in contrast, we study how the detailed sequence structure determines the properties of the emergent cooperative structures. In particular, we study a system of binary polymers, where each polymer can replicate itself by exact ligation of two matching subsequences. We report the emergence of stable cooperative structures with high equilibrated polymer concentrations together with a quantitative connection between the details of the sequence and the frequency as well as the stability of the evolving cooperative structures. These findings could have implications for early earth information polymers as well as the design of protocell information polymer networks. In the simplest realization, we allow for decomposition, random ligation, and autocatalytic ligation of polymers via the three reactions l.m c 0
author_names: Steen Rasmussen

Harold Fellermann

Shinpei Tanaka
title: Sequence selection and evolution in a binary polymer model
venue: ECAL
year: 2013