• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.223-228
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• 2016

A digital micromirror system was proposed for future smart learning. This system is the compact micro-projector with a built-in CMOS sensor modules. It can provide the various interfaces. The basis of interface is to recognize the finger tip on projected image. But the recognition rate of finger tip is very low due to various image degradations. In this paper, we propose the finger tip recognition algorithm that minimize the image degradation factors by using the Retinex transform and IR structuring light. By verifying the availability of the algorithm through experiment, the performance of finger tip recognition was confirmed. Therefore, the user interface can be able to be enhanced significantly in DMS.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.275-284
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• 2008

With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.1-10
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• 2011

In this paper, we proposed the skin color based hand and finger detection technology for the gesture recognition in CCTV surveillance. The aim of this paper is to present the methodology for hand detection and propose the finger detection method. The detected hand and finger can be used to implement the non-contact mouse. This technology can be used to control the home devices such as home-theater and television. Skin color is used to segment the hand region from background and contour is extracted from the segmented hand. Analysis of contour gives us the location of finger tip in the hand. After detecting the location of the fingertip, this system tracks the fingertip by using only R channel alone, and in recognition of hand motions to apply differential image, such as the removal of useless image shows a robust side. We explain about experiment which relates in fingertip tracking and finger gestures recognition, and experiment result shows the accuracy above 96%.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.10-19
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• 1996

This paper presents a finger-shaped multisensor system which can measure the tyep and position of a target surface by contactl. The multi-sensor system consists of a sphere-shpaed optical tactile sensor located at the finger tip and a force/torque sensor located at the joint of a finger. The optial tactile sensor determines the type and position of the target surface using the shape and position of the CCD image of the touching area generated by a contact between the sensor and the taget surface. The force/torque sensor also determines the position and surface normal vector by applying the distributionof forces and torques t the contact point to the equations of finger shape. The measurements on the position and surface normal vector at a contact point obtined by two individual sensors are fused using a statistical method. The integrated sensor system has 0.8mm error in position measurement and 1.31$^{\circ}$ error in normal vector measurement. The developed sensor system has many applications, such as autonomous compliance control, automatic grasping and recognition, etc.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.448-451
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• 1999

In this paper, we propose a new object representation method and matching algorithm for object recognition using a 3-fingered robot hand. Each finger tip can measure normal vector and shapes of a contacting surface. Object is represented by the inter-surface description table where the features of a surface are described in the diagonal and the relations between two surfaces are in the upper diagonal. Based on this table, a fast and the efficient matching algorithm has been proposed. This algorithm can be applied to natural quadric objects.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.374-380
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• 2010

This paper proposes a wearable interface for a tendon-driven robotic hand prosthesis. The proposed interface is composed of a dataglove to measure finger and wrist joint angle, and a micro-control board with a wireless RF module. The interface is used for posture control of the robotic hand prosthesis. The measured joint angles by the dataglove are transferred to the main controller via the wireless module. The controller works for directly controlling the joint angle of the hand or for recognizing hand postures using a pattern recognition method such as LDA and k-NN. The recognized hand postures in this study are the paper, the rock, the scissors, the precision grasp, and the tip grasp. In experiments, we show the performances of the wearable interface including the pattern recognition method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.506-511
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• 2004

Biometrics is getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry has been used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. Hence, it can be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. However, during experimentation, it was discovered that length measured from the tip of the finger was not a reliable feature. Hence, we propose a new technique based on Genetic Algorithm for extraction of the center of nail bottom, in order to use it for the length feature.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.47-54
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• 2010

We propose a smart human-computer interface replacing conventional mouse interface. The interface is able to control cursor and command action with only hand performing without object. Four finger motions(left click, right click, hold, drag) for command action are enough to express all mouse function. Also we materialize cursor movement control using image processing. The measure what we use for inference is entropy of EMG signal, gaussian modeling and maximum likelihood estimation. In image processing for cursor control, we use color recognition to get the center point of finger tip from marker, and map the point onto cursor. Accuracy of finger movement inference is over 95% and cursor control works naturally without delay. we materialize whole system to check its performance and utility.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.347-358
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• 2009

In this thesis, we develop a vision based hand motion recognition system using a camera with two rotational motors. Existing systems were implemented using a range camera or multiple cameras and have a limited working area. In contrast, we use an uncalibrated camera and get more wide working area by pan-tilt motion. Given an image sequence provided by the pan-tilt camera, color and pattern information are integrated into a tracking system in order to find the 2D position and direction of the hand. With these pose information, we estimate 3D motion plane on which the gesture motion trajectory from approximately forms. The 3D trajectory of the moving finger tip is projected into the motion plane, so that the resolving power of the linear gesture patterns is enhanced. We have tested the proposed approach in terms of the accuracy of trace angle and the dimension of the working volume.