• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1725-1731
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• 2004

The use of gestures provides an attractive alternate to cumbersome interface devices for human-computer interaction. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures. The most important issues in gesture recognition are the simplification of algorithm and the reduction of processing time. The mathematical morphology based on geometrical set theory is best used to perform the processing. A key idea of proposed algorithm in this paper is to apply morphological shape decomposition. The primitive elements extracted to a hand gesture include in very important information on the directivity of the hand gestures. Based on this characteristic, we proposed the morphological gesture recognition algorithm using feature vectors calculated to lines connecting the center points of a main-primitive element and sub-primitive elements. Through the experiment, we demonstrated the efficiency of proposed algorithm. Coupling natural interactions such as hand gesture with an appropriately designed interface is a valuable and powerful component in the building of TV switch navigating and video contents browsing system.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.63-68
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• 2018

Interests in face recognition area have been increasing due to diverse emerging applications. Face recognition algorithm from a two-dimensional source could be challenging in dealing with some circumstances such as face orientation, illuminance degree, face details such as with/without glasses and various expressions, like, smiling or crying. Hopfield Network capabilities have been used specially within the areas of recalling patterns, generalizations, familiarity recognitions and error corrections. Based on those abilities, a specific experimentation is conducted in this paper to apply the Redundant Parallel Hopfield Network on a face recognition problem. This new design has been experimentally confirmed and tested to be robust in any kind of practical situations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.109-116
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.283-284
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• 2009

본 논문은 단일 카메라 환경에서 손 형상을 입력정보로 사용하여 손 영역만을 분할한 후 자기 조직화 특징 지도(SOFM: Self Organized Feature Map) 신경망 알고리즘을 이용하여 손 형상을 인식함으로서 수화인식을 위한 보다 안정적이며 강인한 인식 시스템을 구현하고자 한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.245-249
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• 1992

CAD와 CAM 시스템 사이에서 교량역활을 지원하며, 컴퓨터 통합생산(CIM)시스템을 구축하는데 중요한 기능을 수행하는 것 중의하나인 자동공정설계(Computer Aided Process Planning :CAPP) 시스템의 첫 단계는 부품도면에 존재하는 형상 을 인식하는 것이다. 현재까지 개발된 CAPP 시스템 중 CAD 데이타베이스에서 자동적으로 형상인식을 수행하는 시스템 으로는 축대칭인 회전형상 부품을 대상으로하는 시스템이 많이 개발되어 있으나, 비회전형상 부품을 대상으로하는 시스 템은 CAD 데이타베이스의 부적절성으로 인해 제한점이 많은 부분적인 결과만 나와 있을 뿐이다. 본 연구에서는 비회전 형상 부품인 사출금형 부품을 대상으로하여 AutoCAD 시스템을 사용하여 공정설계자의 개입이 없이부품에 존재하는 형상들을 자동적으로 인식하는 알고리즘 개발에 대해서 기술하고자 한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.77-83
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• 2013

In this paper, we suggested a method about the improvement of the voice recognition rate and carried out a study on it. In general, voices were detected by applying the most widely-used method, HMM (Hidden Markov Model) algorithm. Regarding the method of detecting voices, the zero crossing ratio was calculated based on the units of voices before the existence of data was identified. Regarding the method of recognizing voices, the patterns shown by the forms of voices were analyzed before they were compared to the patterns which had already been learned. According to the results of the experiment, in comparison with the recognition rate of 80% shown by the existing HMM algorithm, the suggested algorithm based on the recognition of the patterns shown by the forms of voices showed the recognition rate of 92%, reflecting the recognition rate improved by about 12% compared to the existing one.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.67-75
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• 1999

In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements tat are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have chatacteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.319-326
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• 2009

In this paper, we present an algorithm which recognize hand shape in real time using only image without adhering separate sensor. Hand recognizes using edge orientation histogram, which comes under a constant quantity of 2D appearances because hand shape is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantity, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis(PCA) 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. Human interface system manufacture technique, which controls a home electric appliance or game using, suggested method at experience could be applied.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.33-40
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• 2000

In this study, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements that are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have the characteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• Journal of KIISE:Software and Applications
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• v.27 no.1
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• pp.33-40
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• 2000

Computer Aided Process Planning (CAPP) plays a key role by linking CAD and CAM. Given CAD data of a part, CAPP has to recognize manufacturing features of the part. Despite the long history of research on feature recognition, its research results have rarely been transferred into industry. One of the reasons lies in the separation of feature recognition and process planning. This paper proposes to integrate the two activities through AI techniques, and presents efforts for manufacturable feature recognition, setup minimization, feature dependency construction, and generation of an optimal machining sequence.