• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1686-1694
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• 2014

In this paper, a new scheme to recognize a finger shape in the depth image captured by Kinect is proposed. Rigid transformation of an input finger shape is pre-processed for its robustness against the shape angle of input fingers. After extracting contour map from hand region, observing the change of contour pixel location is performed to calculate rotational compensation angle. For the finger shape recognition, we first acquire three pixel points, the most left, right, and top located pixel points. In the proposed algorithm, we first acquire three pixel points, the most left, right, and top located pixel points for the finger shape recognition, also we use geometrical features of human fingers such as Euclidean distance, the angle of the finger and the pixel area of hand region between each pixel points to recognize the finger shape. Through experimental results, we show that the proposed algorithm performs better than old schemes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.197-201
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• 2011

The use of gestures provides an attractive alternate to cumbersome interfaces for human-computer devices interaction. This has motivated a very active research area concerned with computer vision-based recognition of hand gestures. The most important issues in hand gesture recognition is to recognize the directivity of finger. The primitive elements extracted to a hand gesture include in very important information on the directivity of finger. In this paper, we propose the recognition algorithm of finger directivity by using the cross points of circle and sub-primitive element. The radius of circle is increased from minimum radius including main-primitive element to it including sub-primitive elements. Through the experiment, we demonstrated the efficiency of proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.593-598
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• 2014

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1323-1329
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• 2021

For hand expression recognition, hand pose recognition based on the static shape of the hand and hand gesture recognition based on the dynamic hand movement are used together. In this paper, we propose a hierarchical hand pose model based on finger position and shape for hand expression recognition. For hand pose recognition, a finger model representing the finger state and a hand pose model using the finger state are hierarchically constructed, which is based on the open source MediaPipe. The finger model is also hierarchically constructed using the bending of one finger and the touch of two fingers. The proposed model can be used for various applications of transmitting information through hands, and its usefulness was verified by applying it to number recognition in sign language. The proposed model is expected to have various applications in the user interface of computers other than sign language recognition.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.187-189
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• 2004

This paper presents the system widely used for extraction of human body recognition system in the field of bio-metric identification. The Human body recognition system is used in many fields. This biological is appled to the human recognition in banking and the access control with security. The important algorithm of the identification software usese hand lines and hand shape geometry. We used the simple algorithm and recognizing the person by their hand image from the input camera. The geometrical characteristics in hand shape such as length of finger to whole hand length thickness of finger to length, etc are used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.91-97
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• 2013

A finger-gesture remote controller using the single camera is implemented in this paper, which is base on the recognition of finger number and finger moving direction. Proposed method uses the transformed YCbCr color-difference information to extract the hand region effectively. The number and position of finger are computer by using a double circle tracing method. Specially, a user continuous-command can be performed repeatedly by recognizing the finger-gesture direction of single shape. The position information of finger enables a user command to amplify a same command in the User eXperience. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the our proposed method, after applying to the commercial video player software as a remote controller. As a result, the proposed method showed the average 89% recognition ratio by the user command-mode.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2956-2962
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• 2015

In this paper, we propose a novel algorithm, Concentric-Circle Tracing algorithm, which recognizes finger's shape and counts the number of fingers of hand using low-cost web-camera. We improve algorithm's usability by using low-price web-camera and also enhance user's comfortability by not using a additional marker or sensor. As well as counting the number of fingers, it is possible to extract finger's shape information whether finger is straight or folded, efficiently. The experimental result shows that the finger gesture can be recognized with an average accuracy of 95.48%. It is confirmed that the hand-gesture is an useful method for HCI input and remote control command.

• Journal of KIISE
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• v.43 no.11
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• pp.1307-1314
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• 2016

Virtual Hangul keyboards like Chun-Ji-In, Narat-Gul, and QWERTY are based on eyesight recognition, in which input letter positions are fixed in the smartphone environment. The input method of a fixed-position style is not very convenient for visually impaired individuals. In order to resolve the issue of inconvenience of the Hangul input system, we propose a new paradigm of the finger-touch based Hangul input system that does not need eyesight recognition of input buttons. For the convenience of learning the touch-motion based keyboard, finger touches are designed by considering the shape and frequencies of Hangul vowels and consonants together with the preference of fingers. The base position is decided by the first touch of the screen, and the finger-touch keyboard is used in the same way for all the other touch-style devices, regardless of the differences in size and operation system. In this input method, unique finger-touch motions are assigned for Hangul letters that significantly reduce the input errors.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.42-47
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• 2014

A finger-gesture game controller using the single camera is implemented in this paper, which is based on the recognition of the number of fingers and the index finger moving direction. Proposed method uses the CAMShift algorithm to trace the end-point of index finger effectively. The number of finger is recognized by using a double circle tracing method. Then, HSI color mode transformation is performed for the CAMShift algorithm, and YCbCr color model is used in the double circle tracing method. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the proposed method, we developed a shooting game simulator and validated the proposed method. The proposed method showed the average recognition ratio of more than 90% for each of the game command-mode.