• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.398-405
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• 2018

In the HCI, hand gesture recognition is attracting attention as a method for interaction and information exchange between users and devices along with the development of IT devices. In hand gesture recognition through image processing, palm region detection is a key process contributing to improvement of processing speed and recognition rate. In this paper, we propose a new method for image segmentation between the hand and wrist for palm area detection. The anatomical characteristics of the hand are used to calculate the distance between the iliac bones of the thumb and little finger, which have the widest width, by the horizontal projection histogram of the hand image, and then the palm area is detected by drawing a circle having the width as the diameter. In order to verify the superiority of this method, multiple stage template matching is used to compare and evaluate recognition performance against the four conventional methods for 10 hand gestures. Note that the literatures to offer palm area detection performance evaluation are few although there are many studies on hand gesture recognition.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.70-81
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• 2017

The aim of this study is to understand the effects of a self-leadership program on career recognition and self-efficacy in adolescents under probation. As a result, it was discovered that the self-leadership program had statistically significant differences in self-understanding, the understanding of work and the job world, setting a career goal and strategies in the sub-area of career recognition in adolescents under probation while there was no significant difference in the area of attitudes and values of work. The self-leadership program had statistically significant differences in confidence, self-regulated efficacy among the sub-area of self-efficacy of the subjects while there were no significant differences in the difficulty of the challenge. These results suggest that the self-leadership program had significant effects on career recognition and self-efficacy in adolescents under probation. In order to improve the career recognition and self-efficacy in adolescents under probation, further studies on the self-leadership program are needed and care should be paid to its usability.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.11-19
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• 2016

The personal identification based on the biometrics has emerged as one of the new trend. This study attempted to explore and examine the user recognition in the use of the personal identification based on the biometrics in the respect of self-efficacy, trustiness, security, and safety alongside the effect of the recognition on the future use intention through survey. The result of this study demonstrated the effect on the use intention of the perceived trustiness and ease of the fingerprint identification, perceived ease of the iris identification and the perceived trustiness of the vein identification. The result of this study is expected to suggest direction on the application of the biometrics considering user recognition.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.651-659
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• 2016

The purposes of this study is to investigate the influence of career recognition upon career development competencies and educational needs. To achieve this, the survey was carried out and 362 undergraduates participated. The findings of the survey were shown as follows: First, the students perceived that career management was needed the most, and then came career information searches. Next, career transition technologies, positive self-concept formation, career planning, and effective interpersonal relationships were in order. Second, the influence of career recognition upon the level of the preparations showed statistically significant differences, however, the influence of career recognition upon the level of the requirement did not reveal statistically significant differences. Third, the rating of the educational needs was identical from the first place to the third, but different from the fourth to the sixth. These results will contribute to enhancing the efficiency of career education.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.236-245
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• 2008

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an efficient illumination preprocessing method for face recognition. illumination preprocessing algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing effects of illumination. Due to the result of these improvements, face images preprocessed by the proposed illumination preprocessing method becomes to have more distinctive feature vectors(Gabor feature vectors). Through experiments of face recognition using Gabor jet similarity, the effectiveness of the proposed illumination preprocessing method is verified.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.93-99
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• 2017

A hybrid approach using Long Short Term Memory (LSTM) Recurrent Neural Network (RNN) has showed great improvement in speech recognition accuracy. For training acoustic model based on hybrid approach, it requires forced alignment of HMM state sequence from Gaussian Mixture Model (GMM)-Hidden Markov Model (HMM). However, high computation time for training GMM-HMM is required. This paper proposes an end-to-end approach for LSTM RNN-based Korean speech recognition to improve learning speed. A Connectionist Temporal Classification (CTC) algorithm is proposed to implement this approach. The proposed method showed almost equal performance in recognition rate, while the learning speed is 1.27 times faster.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.79-87
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• 2011

Although products with the fingerprint recognition system currently show a rapid growth in quantity, it is also true that efforts to consider the product quality have been lacking until now. Accordingly, this paper analyzed technological elements with domestic and foreign market situations for products with the fingerprint recognition system to develop an evaluation model to support the quality increase by evaluating aspects of product quality for the knowledge information security, identifying the level of quality and deriving directions for improvements. A model for the reliability quality evaluation was constructed that can be applied comprehensively to non-functional elements that have not been done in the existing evaluations central to the security functions by analyzing requirements for the security, performance and reliability in consideration of features on products. It is considered that this paper can make contributions to the overall quality increase for products with the knowledge information security by reflecting features and trends for the fingerprint recognition products and building a model for the reliability and evaluation to perform evaluations by product.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.198-205
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• 2010

The subjects of this study were 100 female cancer patients in wearing wigs. First survey was before wearing wigs for the female cancer patients who started losing their hair due to the side effect of the anti-cancer and second survey was after a month in wearing wigs. This study was purposed to analyze the recognition change before and after wearing wigs of the female cancer patients who started losing their hair due to the side effect of the anti-cancer. The gathered data were examined and analyzed through frequency analysis, paired t-test based on the recognition change which affect the quality of life before and after wearing wigs, and change of recognition related to the wigs. According to the results of this study, it is necessary to add wearing wigs as additional services in national health insurance and to educate desirable support program for life quality of female cancer patients in hospital.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.25-32
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• 2015

With the increased frequency of crime such as assaults and sexual violence, the reliance on CCTV in arresting criminals has increased as well. However, CCTV, which should be monitored by human labor force at all times, has limits in terms of budget and man-power. Thereby, the interest in intelligent security system is growing nowadays. Expanding the techniques of an objects behavior recognition in previous studies, we propose a system to detect forms of violence between 2~3 objects from images obtained in CCTV. It perceives by detecting the object with the difference operation and the morphology of the background image. The determinant criteria to define violent behaviors are suggested. Moreover, provable decision metric values through measurements of the number of violent condition are derived. As a result of the experiments with the threshold values, showed more than 80% recognition success rate. A future research for abnormal behaviors recognition system in a crowded circumstance remains to be developed.