• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.5
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• pp.332-339
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• 1986

This paper proposes a new method for the normalization of shape pattern based on Gaussian probability density function to increase automatic recognition rate of hand-written Hangul pattern. The sizes of hand-written Hangul pattern are detected from the input images, and pattern sizes are normalized by two variables interpolation. The pattrn shapes are noralized by letting correlation coefficients equal to zero. It is analyzed theoretically and verified through computer simulation for the relation between input image and normaized shape pattern. It is confirmed that this method is effective and reasonable for deformed hand-written Hangul pattern. Experimental resu results show that the declination. size and stroke width of hand-written Hangul patterns are mych improved.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.516-520
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• 2007

This paper presents a intuitive, simple and easy smart home TV remote control system using the hand gesture recognition. Hand candidate regions are detected by cascading policy of the part of human anatomy on the disparity map image, Exact hand region is extracted by the graph-cuts algorithm using the skin color information. Hand postures are represented by shape features which are extracted by a simple shape extraction method. We use the forward spotting accumulative HMMs for a smart home TV remote control system. Experimental results show that the proposed system has a good recognition rate of 97.33 % for TV remote control in real-time.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.8
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• pp.1139-1148
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• 1999

This paper discussed the assessment of hand of denim fabrics finished by enzymatic hydrolysis. The semantic differential scale established using the database collected from university students. Analyzing the subjective rating by common factor analysis with oblimin rotation five factors expressing the hand were induced. Factor one was the surface property related to the surface roughness or softness Factor two was the durability which was related to the compactness and bearing strength Factor three was the sense of weight which was related to the thickness and weight. The moisture related properties and the sense of shape recovery were the forth and fifth factors respectively. the evaluations on the surface property weight and moisture related properties were similar by men and women However the shape recovery and the durability were evaluated differently. Surface and weight related properties were important factors judging the hand of fabrics by both group.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1067-1075
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• 2006

This paper proposes a advanced representation method of hand motion by cheremes analysis in korean sign language. The proposed method is the representation method which apply to the hand motion used in KSL(Korean Sign Language) to represent rich and united hand motion. Words or sentences in KSL are completed by combination of elements called as Cheremes, that is, a hand movement orientation, a finger shape, a hand position, etc. In this paper, Cheremes composing the KSL is divided and represented by 5 elements: the hand movement orientation(HMO), finger shape(FS), hand orientation(HO), hand position(HP) and number of using hand (HN). Each cheremes is expressed by more various characteristics. For example, The hand movement orientation means orientations which the hand move while the sign language is done and can be expressed by 17orientation components. The finger shape means various shapes which fingers can take and represented by 17 components. The Orientation of hand is expressed by 2 characteristics according to whether we use the palm of the hand or the back. The position of hand means specific regions in body which hand(s) is placed while the sign language is done and divided by 8 regions. Finally, the number of hand means whether use only one hand or both hands and is expressed by 2 characteristics. The proposed method has been tested with KSL words and sentences and the results have shown that they can be expressed completely by the proposed representation method.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.805-814
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• 2013

This paper proposes a robust hand segmentation method using view-invariant characteristic of a wrist-mounted camera, and deals with a hand shape recognition system based on segmented hand information. We actively utilize the advantage of the proposed camera device that provides view-invariant images physically, and segment hand region using a Bayesian rule based on adaptive histograms. We construct HSV histograms from RGB histograms, and update HSV histograms using hand region information from a current image. We also propose a user adaptation method by which hand models gradually approach user-dependent models from user-independent models as the user uses the system. The proposed method was evaluated using 16 Korean manual alphabet, and we obtained increases of 27.91% in recognition success rate.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.343-352
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• 2012

In this paper, we implemented a touchless interface for DID(Digital Information Display) system using gesture recognition technique which includes both hand motion and hand shape recognition. Especially this touchless interface without extra attachments gives user both easier usage and spatial convenience. For hand motion recognition, two hand-motion's parameters such as a slope and a velocity were measured as a direction-based recognition way. And extraction of hand area image utilizing YCbCr color model and several image processing methods were adopted to recognize a hand shape recognition. These recognition methods are combined to generate various commands, such as, next-page, previous-page, screen-up, screen-down and mouse -click in oder to control DID system. Finally, experimental results showed the performance of 93% command recognition rate which is enough to confirm the possible application to commercial products.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.267-274
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• 2005

In this paper, we proposed an algorithm which cognize hand pose in real time using only image. Hand recognizes using edge orientation histogram which comes under a constant quantity of 2D appearance because hand pose is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantify, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Besides, principal component space creation time is reduced remarkably because edge directional data is used.

• Journal of Fashion Business
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• v.27 no.4
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• pp.21-37
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• 2023

This study aimed to classify the hand types of adult males aged 20 to 69 years using three-dimensional measurement data from the 2020 8th Korean Anthropometric Survey, the latest measurement data from the National Institute of Standards and Technology Size Korea, and explore the characteristics of each type. Through this, I aimed to draw implications for the development of work gloves. The factors that make up an adult male's hand were categorized into hand and finger thickness factors, palm length factors, and finger length factors. Adult male hands were categorized into four types: small, thin hands and long fingers; thick, long fingers; medium, short hands and fingers; and large, thin, short fingers. The analysis showed that the younger the age, the more slender and long the hands and fingers, and as age increased, hands and fingers became shorter and thicker. Implications for the development of work gloves included the need for size segmentation based on the age of the work glove user, changes in the way glove dimensions are set based on hand length and hand circumference, and the need to segment gloves by the type of work. Hand typing in future research should be done according to occupational groups, and glove patterns should be developed for each type of work based on the results of this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1564-1572
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• 2011

In this paper, we propose a new histogram based hand recognition algorithm for augmented reality. Hand recognition system makes it possible a useful interaction between an user and computer. However, there is difficulty in vision-based hand gesture recognition with viewing angle dependency due to the complexity of human hand shape. A new hand recognition system proposed in this paper is based on the features from hand geometry. The proposed recognition system consists of two steps. In the first step, hand region is extracted from the image captured by a camera and then hand gestures are recognized in the second step. At first, we extract hand region by deleting background and using skin color information. Then we recognize hand shape by determining hand feature point using histogram of the obtained hand region. Finally, we design a augmented reality system by controlling a 3D object with the recognized hand gesture. Experimental results show that the proposed algorithm gives more than 91% accuracy for the hand recognition with less computational power.