• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.589-591
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• 2000

비디오 데이터가 포함하고 있는 카메라와 이동물체의 동작정보를 추출하기 위한 대표적인 방법으로 동작벡터 추출알고리즘이 있다. 본 논문에서는 영상 내에 밝기 값 분포가 균일한 영역이 존재할 때 부정확한 정합 결과를 보이는 것은 기존 알고리즘의 문제점과 이를 개선할 수 있는 계층적 블록정합 알고리즘의 정합오류 전파가능성, 높은 시간복잡도 문제를 동시에 해결할 수 있는 블록정합 알고리즘을 제안한다. 제안하는 알고리즘은 Coarse-to-Fine 방식의 탐색방법과 Dynamic Control Strategy를 결합한 것으로서 정합한 블록의 상황에 따라 탐색 레이어를 동적으로 변경시키는 방법을 사용한다. 본 알고리즘은 크게 두단계로 나뉘어 지는데 탐색 레이어를 결정하는 Control 변경 결정 단계와 정합도 측정함수를 통해 블록에 대한 정합 정확도를 측정하는 단계로 구성이 된다.

• Journal of IKEEE
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• v.23 no.2
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• pp.557-570
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• 2019

In this study, a novel hierarchical approach is investigated to extract coronary vessel from X-ray angiogram. First, we propose to combine Decimation-free Directional Filter Bank (DDFB) and Homographic Filtering (HF) in order to enhance X-ray coronary angiographic image for segmentation purposes. Because the blood vessel ensures that blood flows in only one direction on vessel branch, the DDFB filter is suitable to be used to enhance the vessels at different orientations and radius. In the combination with HF filter, our method can simultaneously normalize the brightness across the image and increases contrast. Next, a coarse-to-fine strategy for iterative segmentation based on Otsu algorithm is applied to extract the main coronary vessels in different sizes. Furthermore, we also propose a new approach to segment very small vessels. Specifically, based on information of the main extracted vessels, we introduce a new method to extract junctions on the vascular tree and level of nodes on the tree. Then, the window based segmentation is applied to locate and extract the small vessels. Experimental results on our coronary X-ray angiography dataset demonstrate that the proposed approach can outperform standard method and attain the accuracy of 71.34%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2669-2688
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• 2016

An efficient and effective unsupervised single moving object detection framework is presented in this paper. Given the sparsely labelled trajectory points, we adopt a coarse-to-fine strategy to detect and segment the foreground from the background. The superpixel level coarse segmentation reduces the complexity of subsequent processing, and the pixel level refinement improves the segmentation accuracy. A distance measurement is devised in the coarse segmentation stage to measure the similarities between generated superpixels, which can then be used for clustering. Moreover, a Quadmap is introduced to facilitate the refinement in the fine segmentation stage. According to the experiments, our algorithm is effective and efficient, and favorable results can be achieved compared with state-of-the-art methods.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.7
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• pp.92-100
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• 1998

In this paper, we suggest a new identification method for sugeno-type fuzzy model via new data clustering strategy. The suggested algorithm is much simpelr than the original identification strategy adopted in. The algorithm suggested in this paper is somewhat similar to that of [2] and [6], that is the algorithm suggested in this paper consists of two steps: coarse tuning and fine tuning. In this paper, double clustering strategy is proposed for coarse tunign. Finally, the resutls of computer simulation are given to demonstrate the validity of this algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.421-441
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• 2021

Fruit detection in orchards is one of the most crucial tasks for designing the visual system of an automated harvesting robot. It is the first and foremost tool employed for tasks such as sorting, grading, harvesting, disease control, and yield estimation, etc. Efficient visual systems are crucial for designing an automated robot. However, conventional fruit detection methods always a trade-off with accuracy, real-time response, and extensibility. Therefore, an improved method is proposed based on coarse-to-fine multitask cascaded convolutional networks (MTCNN) with three aspects to enable the practical application. First, the architecture of Fruit-MTCNN was improved to increase its power to discriminate between objects and their backgrounds. Then, with a few manual labels and operations, synthetic images and labels were generated to increase the diversity and the number of image samples. Further, through the online hard example mining (OHEM) strategy during training, the detector retrained hard examples. Finally, the improved detector was tested for its performance that proved superior in predicted accuracy and retaining good performances on portability with the low time cost. Based on performance, it was concluded that the detector could be applied practically in the actual orchard environment.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.317-320
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• 1999

A robust end time optimal conかof strategy for dual-stage servo system is presented. The time optimal trajectory for a mass-damper system is determined and given os a reference input to the servo system. The feedback controller is constructed so that the fine stage tracks the coarse stage errors and robustly designed as the“perturbation compensated sliding mode control(PCSMC)”law, a combination of slid-ing mode controller(SMC) and perturbation observer(PO). In addition, a null motion controller which regulates the fine stage at its neutral position is designed based on the“dynamic consistency”So, the overall dual-stage servo system exhibits the robust and time-optimal performance. The inherent merit and performance of the dual-stage system will be shown.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1834-1847
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• 2006

A robust minimum-time control (RMTC) strategy is addressed and it is extended to the dual-stage servo design. Rather than conventional switching type sub-optimal controls, it is a reference following control approach where the predetermined minimum-time trajectory (MTT) is tracked by the perturbation compensator based feedback controller. First, the minimum-time trajectory for a mass-damper system is derived. Then, the perturbation compensator to achieve robust tracking performance in spite of model uncertainty and external disturbance is suggested. The RMTC is also applied to the dual-stage positioner which consists of coarse actuator and fine one. To best utilize the actuation redundancy of the dual-stage mechanism, a null-motion controller to actively regulate the relative motion between the two stages is formulated. The performance of RMTC is validated through simulation and experiment.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.527-530
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• 2003

In this paper, we implemented the voxel coloring method to reconstruct 3D object from synthetic input Images. Then compare the result between using standard voxel coloring and using coarse-to-fine method. We compared using different voxel space site to see the difference of time processing and the result of 3D object. Photorealistic 3D object reconstruction is a challenging problem in computer graphics. Vexel coloring considered the reconstruction problem as a color reconstruction problem, instead of shape reconstruction problem. This method works by discretizing scene space into yokels, then traversed and colored those in special order. Also there is an extension of voxel coloring method far decreasing the amount of processing time called coarse-to-fine method. This. method works using low resolution instead of high resolution as input and after processing finish, apply some kind of search strategy.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.4
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• pp.3-9
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• 2007

Existing long range piezoelectric motors with friction based transmission mechanisms are limited by the axial load capacity. To overcome this problem, a new linear piezoelectric motor using one piezoelectric actuator combined with a novel stepping mechanism is reported in this paper. To obtain both long range and fine accuracy, dual positioning control strategy consisting of coarse positioning and fine positioning is used. Coarse positioning is used for long travel range by accumulating motion steps obtained by piezoelectric actuator. This is followed by fine positioning where required accuracy is obtained by fine motion displacement of piezoelectric actuator. This prototype is able to provide resolution of 20 nanometers and withstand a maximum axial load of 300N. At maximum load condition, the positioner can move forward to a travel distance of 5mm at a maximum speed of 0.4 mm/sec. This design of nanopositioner can be used in applications for ultra precision positioning and grinding operations where high axial force capacity is required.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.356-359
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• 1997

Recently many studies have been conducted of fuzzy modeling since it can describe a nonlinear system better than the conventional methods. A famous researcher, M. Sugeno, suggested a fuzzy model which superbly describes a nonlinear system. In this paper, we suggest a new identification method for Sugeno-typo fuzzy model. The suggested algorithm is much simpler than the original identification strategy adopted in [1]. The algorithm suggested in this paper is somewhat similar to that of [2]. that is, the algorithm suggested in this paper consists of two consists of two steps: coarse tuning and fine tuning. In this paper, double clustering strategy is proposed for coarse tuning. Finally, the results of computer simulation are given to demonstrate the validity of this algorithm.