The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher wei...The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm.展开更多
This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulati...This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulation and experimental research on the illumination intensity distribution of several direction parameters.In the experiment,four LED matrixes are identified by LED-ID with room dimensions of 3.75×4.00×2.7 m^3.The results show that the mean of the location error is 0.22 m in the receiving plane,verifying the correctness and feasibility of the positioning scheme.展开更多
The standard gliadin fingerprints and their database of 68 major cultivars and a part of backbone parents, which have ever been extensively grown in North China since the 1950' s, were constructed by using CAWGES ...The standard gliadin fingerprints and their database of 68 major cultivars and a part of backbone parents, which have ever been extensively grown in North China since the 1950' s, were constructed by using CAWGES software and an improved method of pH 3.2 A-PAGE. In the meantime, investigations were made on the utilization of the database in the area of gliadin fingerprints analysis, variety identification and genetic relationship study. The results showed that it provided an effective method for building core collections and variety identification.展开更多
In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this ...In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this paper,a novel approach based on crowd paths to solve this problem is presented,which collects and constructs automatically fingerprints database for anonymous buildings through common crowd customers.However,the accuracy degradation problem may be introduced as crowd customers are not professional trained and equipped.Therefore,we define two concepts:fixed landmark and hint landmark,to rectify the fingerprint database in the practical system,in which common corridor crossing points serve as fixed landmark and cross point among different crowd paths serve as hint landmark.Machinelearning techniques are utilized for short range approximation around fixed landmarks and fuzzy logic decision technology is applied for searching hint landmarks in crowd traces space.Besides,the particle filter algorithm is also introduced to smooth the sample points in crowd paths.We implemented the approach on off-the-shelf smartphones and evaluate the performance.Experimental results indicate that the approach can availably construct WiFi fingerprint database without reduce the localization accuracy.展开更多
Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will resul...Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will result in the decline of positioning accuracy.The widespread extension of Bluetooth positioning is limited by the need of manual effort to collect the fingerprints with position labels for fingerprint database construction and updating.To address this problem,this paper presents an adaptive fingerprint database updating approach.First,the crowdsourced data including the Bluetooth Received Signal Strength(RSS)sequences and the speed and heading of the pedestrian were recorded.Second,the recorded crowdsourced data were fused by the Kalman Filtering(KF),and then fed into the trajectory validity analysis model with the purpose of assigning the unlabeled RSS data with position labels to generate candidate fingerprints.Third,after enough candidate fingerprints were obtained at each Reference Point(RP),the Density⁃based Spatial Clustering of Applications with Noise(DBSCAN)approach was conducted on both the original and the candidate fingerprints to filter out the fingerprints which had been identified as the noise,and then the mean of fingerprints in the cluster with the largest data volume was selected as the updated fingerprint of the corresponding RP.Finally,the extensive experimental results show that with the increase of the number of candidate fingerprints and update iterations,the fingerprint⁃based Bluetooth positioning accuracy can be effectively improved.展开更多
Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich ...Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.展开更多
In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstation...In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset.展开更多
Latent fingerprints are the unintentional impressions found at the crime scenes and are considered crucial evidence in criminal identification.Law enforcement and forensic agencies have been using latent fingerprints ...Latent fingerprints are the unintentional impressions found at the crime scenes and are considered crucial evidence in criminal identification.Law enforcement and forensic agencies have been using latent fingerprints as testimony in courts.However,since the latent fingerprints are accidentally leftover on different surfaces,the lifted prints look inferior.Therefore,a tremendous amount of research is being carried out in automatic latent fingerprint identification to improve the overall fingerprint recognition performance.As a result,there is an ever-growing demand to develop reliable and robust systems.In this regard,we present a comprehensive literature review of the existing methods utilized in latent fingerprint acquisition,segmentation,quality assessment,enhancement,feature extraction,and matching steps.Later,we provide insight into different benchmark latent datasets available to perform research in this area.Our study highlights various research challenges and gaps by performing detailed analysis on the existing state-of-the-art segmentation,enhancement,extraction,and matching approaches to strengthen the research.展开更多
基于接收信号强度指示(received signal strength indicator,RSSI)指纹的定位方法需要预先建立定位区域指纹库,传统静态采集指纹库的建立更新需要大量的人力和时间,并且定位一致性容易受终端差异(如指纹采集手机与定位手机硬件不同导致...基于接收信号强度指示(received signal strength indicator,RSSI)指纹的定位方法需要预先建立定位区域指纹库,传统静态采集指纹库的建立更新需要大量的人力和时间,并且定位一致性容易受终端差异(如指纹采集手机与定位手机硬件不同导致接收信号差异)影响,使得这种方法的大范围推广使用变得异常艰难。针对以上问题,通过移动行走过程中采集的RSSI指纹建立对应的移动采集指纹库,根据移动采集指纹特征构建特征向量,提出移动采集指纹稀疏特征表征,建立基于自适应压缩感知算法的指纹匹配室内定位模型。实验结果表明,指纹采集效率提升了90.83%,平均定位误差为1.96 m,均方根误差为2.75 m,定位一致性差异误差平均提高了32.67%。所提方法在指纹采集效率、定位精度及不同手机的定位一致性方面优于现有算法。展开更多
为提高室内定位的精度和稳定度,提出了基于无迹卡尔曼滤波(Unscented Kalman Filtering,UKF),并融合蓝牙指纹库和行人航位推算(Pedestrian Dead Reckoning,PDR)的室内定位方法。首先,收集不同位置的信号强度数据,构建蓝牙指纹库。其次,...为提高室内定位的精度和稳定度,提出了基于无迹卡尔曼滤波(Unscented Kalman Filtering,UKF),并融合蓝牙指纹库和行人航位推算(Pedestrian Dead Reckoning,PDR)的室内定位方法。首先,收集不同位置的信号强度数据,构建蓝牙指纹库。其次,利用手机内置加速度计、陀螺仪等多传感器融合进行行人航位推算。在此基础上使用UKF进行融合,克服行人航位推算易产生累计误差的缺点,从而实现高精度室内定位,具有成本低、灵敏度高、稳定性好、定位方法简便等特点。最后,仿真实验结果表明了该方法的有效性。展开更多
文摘The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm.
基金supported by ZTE Industry-Academia-Research Cooperation Funds under Grant No.2014ZTE02-12
文摘This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulation and experimental research on the illumination intensity distribution of several direction parameters.In the experiment,four LED matrixes are identified by LED-ID with room dimensions of 3.75×4.00×2.7 m^3.The results show that the mean of the location error is 0.22 m in the receiving plane,verifying the correctness and feasibility of the positioning scheme.
文摘The standard gliadin fingerprints and their database of 68 major cultivars and a part of backbone parents, which have ever been extensively grown in North China since the 1950' s, were constructed by using CAWGES software and an improved method of pH 3.2 A-PAGE. In the meantime, investigations were made on the utilization of the database in the area of gliadin fingerprints analysis, variety identification and genetic relationship study. The results showed that it provided an effective method for building core collections and variety identification.
基金partially sponsored by National Key Project of China (No.2012ZX03001013-003)
文摘In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this paper,a novel approach based on crowd paths to solve this problem is presented,which collects and constructs automatically fingerprints database for anonymous buildings through common crowd customers.However,the accuracy degradation problem may be introduced as crowd customers are not professional trained and equipped.Therefore,we define two concepts:fixed landmark and hint landmark,to rectify the fingerprint database in the practical system,in which common corridor crossing points serve as fixed landmark and cross point among different crowd paths serve as hint landmark.Machinelearning techniques are utilized for short range approximation around fixed landmarks and fuzzy logic decision technology is applied for searching hint landmarks in crowd traces space.Besides,the particle filter algorithm is also introduced to smooth the sample points in crowd paths.We implemented the approach on off-the-shelf smartphones and evaluate the performance.Experimental results indicate that the approach can availably construct WiFi fingerprint database without reduce the localization accuracy.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61771083,61704015)the Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT1299)+3 种基金the Special Fund of Chongqing Key Laboratory(CSTC)Fundamental Science and Frontier Technology Research Project of Chongqing(Grant Nos.cstc2017jcyjAX0380,cstc2015jcyjBX0065)the Scientific and Technological Research Foundation of Chongqing Municipal Education Commission(Grant No.KJ1704083)the University Outstanding Achievement Transformation Project of Chongqing(Grant No.KJZH17117).
文摘Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will result in the decline of positioning accuracy.The widespread extension of Bluetooth positioning is limited by the need of manual effort to collect the fingerprints with position labels for fingerprint database construction and updating.To address this problem,this paper presents an adaptive fingerprint database updating approach.First,the crowdsourced data including the Bluetooth Received Signal Strength(RSS)sequences and the speed and heading of the pedestrian were recorded.Second,the recorded crowdsourced data were fused by the Kalman Filtering(KF),and then fed into the trajectory validity analysis model with the purpose of assigning the unlabeled RSS data with position labels to generate candidate fingerprints.Third,after enough candidate fingerprints were obtained at each Reference Point(RP),the Density⁃based Spatial Clustering of Applications with Noise(DBSCAN)approach was conducted on both the original and the candidate fingerprints to filter out the fingerprints which had been identified as the noise,and then the mean of fingerprints in the cluster with the largest data volume was selected as the updated fingerprint of the corresponding RP.Finally,the extensive experimental results show that with the increase of the number of candidate fingerprints and update iterations,the fingerprint⁃based Bluetooth positioning accuracy can be effectively improved.
基金supported by Jiangsu Province Key Research and Development Program(BE2018704)Technical Innovation Project of The Ministry of Public Security(20170001)+1 种基金Fundamental Research Funds for the Central Universities(2242022k30001)National Science Foundation of China(CN)(Grant No.61871111).
文摘Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.
文摘In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset.
文摘Latent fingerprints are the unintentional impressions found at the crime scenes and are considered crucial evidence in criminal identification.Law enforcement and forensic agencies have been using latent fingerprints as testimony in courts.However,since the latent fingerprints are accidentally leftover on different surfaces,the lifted prints look inferior.Therefore,a tremendous amount of research is being carried out in automatic latent fingerprint identification to improve the overall fingerprint recognition performance.As a result,there is an ever-growing demand to develop reliable and robust systems.In this regard,we present a comprehensive literature review of the existing methods utilized in latent fingerprint acquisition,segmentation,quality assessment,enhancement,feature extraction,and matching steps.Later,we provide insight into different benchmark latent datasets available to perform research in this area.Our study highlights various research challenges and gaps by performing detailed analysis on the existing state-of-the-art segmentation,enhancement,extraction,and matching approaches to strengthen the research.
文摘为提高室内定位的精度和稳定度,提出了基于无迹卡尔曼滤波(Unscented Kalman Filtering,UKF),并融合蓝牙指纹库和行人航位推算(Pedestrian Dead Reckoning,PDR)的室内定位方法。首先,收集不同位置的信号强度数据,构建蓝牙指纹库。其次,利用手机内置加速度计、陀螺仪等多传感器融合进行行人航位推算。在此基础上使用UKF进行融合,克服行人航位推算易产生累计误差的缺点,从而实现高精度室内定位,具有成本低、灵敏度高、稳定性好、定位方法简便等特点。最后,仿真实验结果表明了该方法的有效性。
