• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1958-1959
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• 2006

This paper proposes a local path-planning algorithm that enables a mobile robot with vision sensor in a local area.The proposed method based on projective geometry and a wavefront method finds local-paths to avoid collisions using 3-D walls or obstacles map generated using projective geometry. Simulation results show the feasibility of the proposed method

• 한국지리정보학회지
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• 제2권2호
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• pp.1-8
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• 1999

세선화 결과에서 원래 선의 굵기 정보는 도면 자동 벡터화 시스템을 구현하는데 유용하게 사용될 수 있다. 본 연구는 세선화 결과에서 원래 선의 굵기 정보를 표현할 수 있는 세선화의 전처리 기법을 제안하였다. 제안된 기법에서는 입력 도면에서 선을 구성하는 각 화소들에 대해서 그것이 주변화소들로부터 둘러싸인 정도를 나타내는 깊이를 계산하고, 세선화 결과에서 골격선의 깊이 정보를 보고 원래 선의 굵기를 알 수 있게 하였다. 제안된 기법을 구현하여 등고선에 대해 실험한 결과, 골격선의 깊이 정보로부터 그 선이 주곡선인지 계곡선인지 쉽게 구별할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.391-411
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• 2023

Aggregates play the skeleton and supporting role in the construction field, high-precision measurement and high-efficiency analysis of aggregates are frequently employed to evaluate the project quality. Aiming at the unbalanced operation time and segmentation accuracy for multi-class segmentation algorithms of aggregate images, a Chaotic Sparrow Search Algorithm (CSSA) is put forward to optimize it. In this algorithm, the chaotic map is combined with the sinusoidal dynamic weight and the elite mutation strategies; and it is firstly proposed to promote the SSA's optimization accuracy and stability without reducing the SSA's speed. The CSSA is utilized to optimize the popular multi-class segmentation algorithm-Multiple Entropy Thresholding (MET). By taking three METs as objective functions, i.e., Kapur Entropy, Minimum-cross Entropy and Renyi Entropy, the CSSA is implemented to quickly and automatically calculate the extreme value of the function and get the corresponding correct thresholds. The image adaptive multi-class segmentation model is called CSSA-MET. In order to comprehensively evaluate it, a new parameter I based on the segmentation accuracy and processing speed is constructed. The results reveal that the CSSA outperforms the other seven methods of optimization performance, as well as the quality evaluation of aggregate images segmented by the CSSA-MET, and the speed and accuracy are balanced. In particular, the highest I value can be obtained when the CSSA is applied to optimize the Renyi Entropy, which indicates that this combination is more suitable for segmenting the aggregate images.

• 대한가정학회지
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• 제35권4호
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• pp.79-94
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• 1997

This study was performed to develop a basic stacks pattern for middle-aged women reflecting the characteristics of their lower body types. Anthropometric measurements using sliding guage method were carried out for 4 women 40's For the analysis of the lower body types horizontal and vertical section maps obtained by sliding gauge method and 2 indices were produced. Based on the slacks construction components produced by the drafts of their lower body surface experimental slacks pattern was designed. Multiple comparison test was used to compare 3 existing slacks patterns with the experimental pattern. 1. The results of the body section map analysis were as follows: 1) In the frontal view silhouette of vertical section maps there were less individual differences in items with skeleton landmarks than those without them. 2) In the shape of horizontal section maps waist section represented more round shape than the others and thigh maximum width section had the flattest shape. Flat ratios(depth/width) of subjects were much higer than those of young women which clarified the change of depth was bigger than that of width with aging process. 2. The slacks construction components for pattern drafting were as follows: 1)Ease amount of waist was 0.5cm and front and back waist girth difference was 1.2cm Ease amount of hip was 1,8cm and front and back hip girth difference was 0.7 cm 2) The amount of dart intake incresed in the order of side(4cm) back(3,6cm) from (2.8cm) The length of dart leg incresed in the order of front side back.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3136-3150
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• 2015

A vision-based 3D tracking of articulated human hand is one of the major issues in the applications of human computer interactions and understanding the control of robot hand. This paper presents an improved approach for tracking and recovering the 3D position and orientation of a human hand using the Kinect sensor. The basic idea of the proposed method is to solve an optimization problem that minimizes the discrepancy in 3D shape between an actual hand observed by Kinect and a hypothesized 3D hand model. Since each of the 3D hand pose has 23 degrees of freedom, the hand articulation tracking needs computational excessive burden in minimizing the 3D shape discrepancy between an observed hand and a 3D hand model. For this, we first created a 3D hand model which represents the hand with 17 different parts. Secondly, Random Forest classifier was trained on the synthetic depth images generated by animating the developed 3D hand model, which was then used for Haar-like feature-based classification rather than performing per-pixel classification. Classification results were used for estimating the joint positions for the hand skeleton. Through the experiment, we were able to prove that the proposed method showed improvement rates in hand part recognition and a performance of 20-30 fps. The results confirmed its practical use in classifying hand area and successfully tracked and recovered the 3D hand pose in a real time fashion.