• Title/Summary/Keyword: finger recognition

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The Implementation of Web Services System for Realtime Finger Recognition in Mobile Environments (모바일 환경에서 실시간 지문인식을 위한 웹 서비스 시스템 구현)

  • Ko, You-Jung;Kim, Yoon-Joong
    • Proceedings of the Korea Contents Association Conference
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    • 2006.11a
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    • pp.483-487
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    • 2006
  • In this paper implemented that PDA sends finger images and can finger recognition web service system in realtime. Finger recognition web service system received the finger images and return the recognition result as XML style. because of this it can offer the same service to using wireless PDA as well as using wire internet client. This system consist of mobile client and finger recognition web service provider. Mobile client request finger recognition web service provider using DIME with taken finger image. We can easily receive and see the result of finger recognition without mass finger database in limited storage space of PDA. Finger recognition web service provider offers that receiving finger images and calling finger recognition system after the recognition return the result.

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New Finger-vein Recognition Method Based on Image Quality Assessment

  • Nguyen, Dat Tien;Park, Young Ho;Shin, Kwang Yong;Park, Kang Ryoung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.2
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    • pp.347-365
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    • 2013
  • The performance of finger-vein recognition methods is limited by camera optical defocusing, the light-scattering effect of skin, and individual variations in the skin depth, density, and thickness of vascular patterns. Consequently, all of these factors may affect the image quality, but few studies have conducted quality assessments of finger-vein images. Therefore, we developed a new finger-vein recognition method based on image quality assessment. This research is novel compared with previous methods in four respects. First, the vertical cross-sectional profiles are extracted to detect the approximate positions of vein regions in a given finger-vein image. Second, the accurate positions of the vein regions are detected by checking the depth of the vein's profile using various depth thresholds. Third, the quality of the finger-vein image is measured by using the number of detected vein points in relation to the depth thresholds, which allows individual variations of vein density to be considered for quality assessment. Fourth, by assessing the quality of input finger-vein images, inferior-quality images are not used for recognition, thereby enhancing the accuracy of finger-vein recognition. Experiments confirmed that the performance of finger-vein recognition systems that incorporated the proposed quality assessment method was superior to that of previous methods.

Reflection-type Finger Vein Recognition for Mobile Applications

  • Zhang, Congcong;Liu, Zhi;Liu, Yi;Su, Fangqi;Chang, Jun;Zhou, Yiran;Zhao, Qijun
    • Journal of the Optical Society of Korea
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    • v.19 no.5
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    • pp.467-476
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    • 2015
  • Finger vein recognition, which is a promising biometric method for identity authentication, has attracted significant attention. Considerable research focuses on transmission-type finger vein recognition, but this type of authentication is difficult to implement in mobile consumer devices. Therefore, reflection-type finger vein recognition should be developed. In the reflection-type vein recognition field, the majority of researchers concentrate on palm and palm dorsa patterns, and only a few pay attention to reflection-type finger vein recognition. Thus, this paper presents reflection-type finger vein recognition for biometric application that can be integrated into mobile consumer devices. A database is built to test the proposed algorithm. A novel method of region-of-interest localization for a finger vein image is introduced, and a scheme for effectively extracting finger vein features is proposed. Experiments demonstrate the feasibility of reflection-type finger vein recognition.

Analysis of Characteristics of Finger-Print Recognition According to Computer Generated Hologram and Its Reconstructed Image (컴퓨터 형성 홀로그램 및 재생 영상에 따른 지문 인식 특성 분석)

  • Jeong, Man-Ho
    • Korean Journal of Optics and Photonics
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    • v.20 no.2
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    • pp.76-80
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    • 2009
  • Finger-print recognition is achieved by comparing an input finger-print image with the stored images in the computer, and finally by determining agreement or disagreement. Encryption and decryption are necessary in the finger-print recognition process. In these process CGH (Computer Generated Hologram) is used, and finger-print images reconstructed from the CGHs are compared. In this paper, two methods of recognition are used, one is to compare the finger-print images of each other reconstructed from their CGHs and the other is to compare the CGHs to each other directly, to analyze the differences of finger-print recognition capability between these two methods. Experimental results show that the capability of finger-print recognition for comparing the CGHs of the two is about 150 times higher than in case of comparing the reconstructed finger-print images. Especially the changes of characteristics according to modulation types of CGH are analyzed.

Finger Vein Recognition based on Matching Score-Level Fusion of Gabor Features

  • Lu, Yu;Yoon, Sook;Park, Dong Sun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.2
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    • pp.174-182
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    • 2013
  • Most methods for fusion-based finger vein recognition were to fuse different features or matching scores from more than one trait to improve performance. To overcome the shortcomings of "the curse of dimensionality" and additional running time in feature extraction, in this paper, we propose a finger vein recognition technology based on matching score-level fusion of a single trait. To enhance the quality of finger vein image, the contrast-limited adaptive histogram equalization (CLAHE) method is utilized and it improves the local contrast of normalized image after ROI detection. Gabor features are then extracted from eight channels based on a bank of Gabor filters. Instead of using the features for the recognition directly, we analyze the contributions of Gabor feature from each channel and apply a weighted matching score-level fusion rule to get the final matching score, which will be used for the last recognition. Experimental results demonstrate the CLAHE method is effective to enhance the finger vein image quality and the proposed matching score-level fusion shows better recognition performance.

Recognition of Finger Language using Image from PC Camera (PC 카메라에서 추출한 이미지를 이용한 수화인식)

  • Lee, Byoung-Hwan;Lee, Kee-Seong
    • Proceedings of the KIEE Conference
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    • 2004.05a
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    • pp.102-104
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    • 2004
  • Finger language is a typical tool for deaf persons. But learning the finger language for non-handicapped persons is very difficult. To overcome these difficulties, a new communication method using visual function is developed recently. Even though the developed system uses the visual function, it needs expensive equipments such as camera and computer. To be used in the real environments, the cost of equipments is a critical factor. If the recognition system for the finger language can be developed with low price equipments, the system can be used in the notebook or cellular phone. The image captured by PC camera was processed by preprocessing algorithm. To recognize the finger language, the resulting image was divide into $5{\times}5$ sections. The recognition system uses a similarity method and position information. The simulation results shows the effectiveness of the proposed algorithm.

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A Study on Finger-click Recognition of a Wearable Input Device using Inertial Sensors (관성 센서를 이용한 착용형 공간 입력장치의 클릭 인식에 관한 연구)

  • Soh, Byung-Seok;Kim, Yoon-Sang;Lee, Sang-Goog
    • Proceedings of the KIEE Conference
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    • 2004.05a
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    • pp.120-122
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    • 2004
  • Wearable input device that can make free-space typewriting possible is introduced. We named this device as $SCURRY^{TM}$. To measure the angular velocity of hand and the acceleration rates at the ends of fingers, we buried MEMS inertial sensors in this keyboard. We processed sensor signals to get the information on hand movement and finger-click motion. With this signal processing, apparent finger movements were depicted over the virtual keyboard shown on output device of a target computing system. In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger clicking of $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click part, and cross-talk avoidance part. The experiments were conducted to verify the effectiveness and efficiency of the proposed algorithms.

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Selective control of multiple devices via finger recognition (다중 디바이스에서 손 인식을 통한 선택적 제어)

  • Chang, Ho-Jung;Kim, Tae-Hyun;Yoon, Youngmi
    • Journal of Korea Multimedia Society
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    • v.17 no.1
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    • pp.60-68
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    • 2014
  • Extensive researches on PC control system via interaction between PC and users are being conducted recently, especially on human finger recognition in the electronic devices. Heretofore, researches on methods to improve the accuracy of finger recognition in a single device and to control the devices with it have been the mainstream, whereas many different industries where finger recognition become more utilized are demanding researches on methods to selectively control the system of multiple devices for applications in various environments and situations. This article demonstrates attempts to selectively control one of two devices through finger recognition. Along with this, experiments conducted with 6 variable conditions are demonstrated here, where the optimal condition to increase the rate of successful selective finger recognition between two devices is studied.

Vision- Based Finger Spelling Recognition for Korean Sign Language

  • Park Jun;Lee Dae-hyun
    • Journal of Korea Multimedia Society
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    • v.8 no.6
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    • pp.768-775
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    • 2005
  • For sign languages are main communication means among hearing-impaired people, there are communication difficulties between speaking-oriented people and sign-language-oriented people. Automated sign-language recognition may resolve these communication problems. In sign languages, finger spelling is used to spell names and words that are not listed in the dictionary. There have been research activities for gesture and posture recognition using glove-based devices. However, these devices are often expensive, cumbersome, and inadequate for recognizing elaborate finger spelling. Use of colored patches or gloves also cause uneasiness. In this paper, a vision-based finger spelling recognition system is introduced. In our method, captured hand region images were separated from the background using a skin detection algorithm assuming that there are no skin-colored objects in the background. Then, hand postures were recognized using a two-dimensional grid analysis method. Our recognition system is not sensitive to the size or the rotation of the input posture images. By optimizing the weights of the posture features using a genetic algorithm, our system achieved high accuracy that matches other systems using devices or colored gloves. We applied our posture recognition system for detecting Korean Sign Language, achieving better than $93\%$ accuracy.

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A Method for Finger Vein Recognition using a New Matching Algorithm (새로운 정합 알고리즘을 이용한 손가락 정맥 인식 방법)

  • Kim, Hee-Sung;Cho, Jun-Hee
    • Journal of KIISE:Software and Applications
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    • v.37 no.11
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    • pp.859-865
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    • 2010
  • In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.