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A New algorithm for Locating and Extracting Minutiae from fingerprint Images

PATTERN RECOGNITION AND IMAGE ANALYSIS 2019年第2期29卷 268-279页

作者： Al-Refoa, A. Alshraideh, M. Sharieh, A. Jordan Univ King Abdulla II Sch Informat Technol Comp Sci Dept Amman 11942 Jordan

fingerprints are considered as the oldest and most widely used in the world for biometric identification. Every person has unique and permanent fingerprints. Most automatic fingerprint recognition systems are based on features formed from lines known as minutiae. Building a database of unique minutiae is very important in the security systems because it concerns the identification of the person committing a crime through the latent left in the crime scene. This research presents a new algorithm to give a minutia a unique value leading to accelerating the search process for a person. The algorithm splits the fingerprint image into four sections, then calculates the values for each minutia in each section and stores it in a database that is designed for this purpose. This research provides a great opportunity and additional options to fingerprint experts in order to solve many cases that are still undiscovered while searching for the latent in the database of minutiae. The results of testing this algorithm were very successful, very encouraging and helpful to fingerprint experts in their work.

关键词： fingerprints minutiae location database of fingerprint images fingerprint algorithm

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Accurate Indoor Localization with IoT Devices and Advanced fingerprinting Methods

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algorithmS 2024年第12期17卷 544-544页

作者： Khodamoradi, Farshad Rezazadeh, Javad Ayoade, John Islamic Azad Univ Elect Tehran Branch Tehran *** Iran Crown Inst Higher Educ CIHE Sydney NSW 2060 Australia

The Internet of things (IoT) has significantly impacted various sectors, including healthcare, environmental monitoring, transportation, and commerce, by enhancing communication networks through the integration of sensors, software, and hardware. This paper presents an accurate IoT indoor localization system based on IoT devices and fingerprinting methods. We explore indoor localization techniques using Bluetooth Low Energy (BLE) and a Radio Signal Strength Indicator (RSSI) to address the limitations of GPS in indoor environments. The study evaluates the effectiveness of iBeacon transmitters for indoor positioning, comparing the Weighted Centroid Localization (WCL) and Positive Weighted Centroid Localization (PWCL) algorithms, along with fingerprinting methods enhanced by outlier detection and mapping filters. Our methodology includes mapping a real environment onto a coordinate axis, collecting training data from 47 sampling points, and implementing four localization algorithms. The results show that the PWCL algorithm improves accuracy over the WCL algorithm, and hybrid methods further reduce localization errors. The HYBRID-MAPPED method achieves the highest accuracy, with an average error of 1.44 m.

关键词： location IoT internal location fingerprint algorithm

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fingerprint Authentication for Budget Application 15

Fingerprint Authentication for Budget Application

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15th International Conference on Engineering of Modern Electric Systems (EMES)

作者： Costea, Naomi Estera Moisi, Elisa Valentina Univ Oradea Fac Elect Engn & Informat Technol Dept Comp Sci & Informat Technol Oradea Romania

ISBN: (纸本)9781728107738

Security has become an increasingly popular domain in computer science. Because today devices are attacked not only by classical viruses but also intentional attacks occur, in order to stole data from devices and obtain material benefits, it is necessary to add new security types. These new ways of securing applications include technologies such as facial recognition, iris recoil, fingerprint recognition. fingerprint algorithms have been embedded in modern mobile devices, for authentication. Nowadays mobile devices use a fingerprint scanner, so fingerprinting algorithms are becoming more widespread. This paper presents a fingerprint authentication algorithm based on the Advance Encryption Standard (AES) and on the Android Keystore System. The proposed algorithm is tested, by integrating it into a budget application.

关键词： fingerprint Biometric Password Android Budget Management Recognition Image Processing Authentication Authentication with fingerprint fingerprint algorithm AES Android Keystore

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Research on Indoor fingerprint Localization System Based on Voronoi Segmentation

Research on Indoor Fingerprint Localization System Based on ...

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International Conference on Life System Modeling and Simulation (LSMS) / International Conference on Intelligent Computing for Sustainable Energy and Environment (ICSEE)

作者： Li, Ang Fu, Jingqi Shen, Huaming Shanghai Univ Dept Automat Coll Mechatron Engn & Automat 149 Yanchang Rd Shanghai 200072 Peoples R China

ISBN: (纸本)9789811063701;9789811063695

The location of entities in a smart indoor environments is an important context information. To this end, several indoor localization algorithm have been proposed with the received signal strength fingerprint (RSS-F) based algorithm being the most attractive due to the higher localization accuracy. However, RSS-F based localization accuracy is highly degraded on account of non-line-of-sight (NLOS) propagation in indoor or harsh environment. This thesis proposes an approach for NLOS self-monitoring and autonomous compensation. Firstly, the localization area is regionalized according to Voronoi Diagram. Then, the self-monitoring and autonomous compensation is realized by propagation environment similarity represented by the dynamic path attenuation index between the domains. The verification experiment results show that the proposed algorithms can adaptively identify the NLOS interference and accomplish compensation. Compared with other localization algorithm, the maximum error is reduced from 3.04 m to 1.71 m, the average error is reduced to 0.90 m, and the localization time is reduced to 2.113 s (contain 10 test point) compared with other tracking algorithm.

关键词： Indoor localization Voronoi diagram fingerprint algorithm

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WiFi Based Indoor Localization with Multiple Kernel Learning 8

WiFi Based Indoor Localization with Multiple Kernel Learning

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8th IEEE International Conference on Communication Software and Networks (ICCSN)

作者： Fan, Heng Chen, Zhongmin Huazhong Agr Univ Coll Engn Wuhan Peoples R China

ISBN: (纸本)9781509017812

To solve the problem of low accuracy in real-time localization in indoor environment, we propose a novel localization algorithm with Multiple Kernel Learning (MKL). In our work, the indoor localization is viewed as multiple classification. First we select some reference nodes in the indoor area, and measure the WiFi signal strength of reference nodes for multiple times to construct the classifiers based on multiple kernel learning. When the object enters into the location area, we measure its WiFi signal strength and input it into classifiers to discriminate its label. According to the classification result, the location of the object can be estimated. Experimental results demonstrate that our algorithm is able to effectively locate the object in indoor environment.

关键词： WiFi localization indoor localization Multiple Kernel Learning (MKL) fingerprint algorithm

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WiFi Based Indoor Localization with Multiple Kernel Learning

WiFi Based Indoor Localization with Multiple Kernel Learning

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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Heng Fan Zhongmin Chen College of Engineering Huazhong Agricultural University

To solve the problem of low accuracy in real-time localization in indoor environment,we propose a novel localization algorithm with Multiple Kernel Learning(MKL).In our work,the indoor localization is viewed as multiple *** we select some reference nodes in the indoor area,and measure the WiFi signal strength of reference nodes for multiple times to construct the classifiers based on multiple kernel *** the object enters into the location area,we measure its WiFi signal strength and input it into classifiers to discriminate its *** to the classification result,the location of the object can be *** results demonstrate that our algorithm is able to effectively locate the object in indoor environment.

关键词： WiFi localization indoor localization Multiple Kernel Learning(MKL) fingerprint algorithm

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Hybrid wireless indoor positioning with iBeacon and Wi-Fi

Hybrid wireless indoor positioning with iBeacon and Wi-Fi

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11th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2015)

作者： Tao Peng Xinhong Wang Chao Wang Danqing Shi Broadband Wireless Communication and Multimedia Laboratory School of Electronics and Information Engineering Tongji University Shanghai China

ISBN: (纸本)9781510821279

The fingerprint of location can reach high precision and high accuracy with the assistance of complex positioning algorithms. However, the indoor environment is complex so that the accuracy of indoor positioning is affected easily and seriously by several kinds of signal interference. In this paper, we use iBeacon as anchor method to help WiFi positioning algorithms. In the hybrid algorithms, iBeacon divides the space into different parts, with the combined iBeacon and Wi-Fi offline fingerprint data, and then it locates partly. Compared to the single Wi-Fi indoor positioning algorithms, it can significantly reduce the amount of calculation and the error of positioning.

关键词： fingerprint algorithm Hybrid algorithm Indoor Positioning Wi-Fi iBeacon Wi-Fi Patient Positioning

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One Reduction Method of Telecommunications Nework Events

One Reduction Method of Telecommunications Nework Events

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2nd International Conference on Advanced Measurement and Test (AMT 2011)

作者： Dong, Chenggen Wu, Jinpei Zhang, Qishan Beihang Univ Beijing Peoples R China

ISBN: (纸本)9783037851975

In this paper, the mass events of telecommunication network are researched, the none fault events reduction method and repeat events reduction method are proposed after researching the events of telecommunications network, on the basis of researching the characteristics of the events of telecommunications network, the improved methods were proposed. Further, in the aspect of event reduction performance, proposed the fingerprint algorithm, the events reduction process of inefficient much text comparison convert efficient integer value comparison, effectively improve the performance of the event reduction, meets real-time event handling performance requirements.

关键词： telecommunications network management none fault events reduction repeat events reduction fingerprint algorithm

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Performance Evaluation of Active RFID Real Time Location System Based On RSSI

Performance Evaluation of Active RFID Real Time Location Sys...

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The 2010 IEEE International Conference on Progress in Informatics and Computing

作者： Zhenting Xiang,Dong Wang Logistic&RFID lab Shanghai Jiaotong University Shanghai,China

In this paper,an active RFID real time location system based on fingerprint algorithm was *** typical scenarios were chosen including ideal environment and complex environment to test the performance of the location *** parameters were considered while evaluate the performance of the location ***,the result shows the performance in different conditions.

关键词： fingerprint algorithm figureprint database reference point

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Orientation-Aware Indoor Localization Path Loss Prediction Model for Wireless Sensor Networks

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2nd International Conference on Network-Based Information Systems (NBiS 2008)

作者： Lihan, Marc Tsuchiya, Takeshi Koyanagi, Keiichi Waseda Univ Grad Sch Informat Prod & Syst Wakamatsu Ku Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9783540856924

There have been a large amount of research and interest in the area of ubiquitous and indoor location aware computing ill the past decade. Anion g several proposed algorithms, fingerprint algorithm stands as one of the most accurate systems for localization. However, there is a lack of theoretical basis and understanding on the orientation of the user. This paper presents a model for orientation-aware indoor location tracking system using a Zigbee based protocol wireless sensor called Sun's SPOT (Small Programmable Object Technology). Our experiment. shows better accuracy in location tracking when orientation acid attenuation factors are considered for the path loss prediction model than the traditional path loss model. Orientation-aware fingerprint algorithm is also examined in our experiment to have a. basis of comparison on an empirical algorithm.

关键词： indoor localization RSS path loss model WSN fingerprint algorithm ZigBee tracking system

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