• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.183-186
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• 2000

영상 분할(image segmentation)은 주어진 영역에서 의미 있는 영역만을 분리해 내는 과정으로 컴퓨터 비젼 분야에 있어 매우 중요한 단계로 취급되어 진다. 본 연구에서는 기존의 영상 분할 알고리즘들의 문제점을 해결하고자 단계적인 marker 영상을 적용한 watershed 알고리즘을 제안하였다. 제안한 방법은 단계적인 level의 조절에 따라 분할의 정도를 선택할 수 있으며 watershed 알고리즘의 특성인 정확한 물체 검출의 장점들 살릴 수 있다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.210-216
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• 2010

In this study, we propose a novel method to segment an individual tooth region in a true color image. The difference of the intensity in RGB is initially extracted and subsequent morphological reconstruction is applied to minimize the spurious segmentation regions. Multiple seeds in the tooth regions are chosen by searching regional minima and a Sobel-mask edge operations is performed to apply MCWA(Marker-Controlled Watershed Algorithm). As the results of applying MCWA transform for our proposed tooth segmentation algorithm, the individual tooth region can be resolved in a CCD tooth color image.

• Journal of Environmental Science International
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• v.24 no.11
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• pp.1473-1483
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• 2015

In this study, a digital terrain analysis had been performed for a mountainous watershed having wetlands. In order to consider the impact for wetland in the flow determination algorithm, the Laplace equation is implemented into the upslope accounting algorithm of wetness computation scheme. The computational algorithm of wetland to spatial contribution of downslope area and wetness was also developed to evaluate spatially distributed runoff due to the presence of wetland. Developed schemes were applied to Wangpichun watershed located Chuncuk mountain at Ulzingun, South Korea. Both spatial distribution of wetness and its histogram indicate that the developed scheme provides feasible consideration of wetland impact in spatial hydrologic analysis. The impact of wetland to downslope propagation pattern is also useful to evaluate spatially distributed runoff distribution.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.81-87
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• 2022

In this paper, we propose a watershed algorithm that applies a high-frequency enhancement filter to emphasize the boundary and a local adaptive threshold to search for minimum points. The previous method causes the problem of over-segmentation, and over- segmentation appears around the boundary of the object, creating an inaccurate boundary of the region. The proposed method applies a high-frequency enhancement filter that emphasizes the high-frequency region while preserving the low-frequency region, and performs a minimum point search to consider local characteristics. When merging regions, a fixed threshold is applied. As a result of the experiment, the proposed method reduced the number of segmented regions by about 58% while preserving the boundaries of the regions compared to when high frequency emphasis filters were not used.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1463-1473
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• 2010

In this paper, we propose a modified watershed algorithm to extract more correct edge and reduce processing time. Two new algorithms are proposed in this paper. The first one is applying two conventional watershed expansion methods known as rainfall and immersion simulation jointly. We analyze the advantage and problem of each simulation and then propose a new expansion method that keeps the advantage and removes the problem in order to extract more correct edge and reduce processing time. The second is a new priority decision algorithm to obtain more correct edge of a region. Some zero-crossing points of gradient are expected to be edge of a region but the conventional method has a limitation that it cannot extract those points as edge. Therefore we propose a new priority decision algorithm for watershed in order to get more correct edge. We compare the proposed method with the conventional method through experiments and prove that the proposed method can extract more correct edge of region.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.156-169
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• 1997

This paper proposes an image segmentation technique using watershed algorithm followed by region merging method. A gradient image is obtained by applying multiscale gradient algorithm to the image simplified by morphological filters. Since the watershed algorithm produces the oversegmented image. it is necessary to merge small segmented regions as wel]' as region having similar characteristics. For region merging. we utilize the merging criteria based on both the mean value of the pixels of each region and the edge intensities between regions obtained by the contour following process. Experimental results show that the proposed method produces meaningful image segmentation results.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.311-318
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• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.2
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• pp.1-10
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• 2003

This paper presents an efficient method for image segmentation based on a multiresolution application of a wavelet transform and watershed segmentation algorithm. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region merging and region projection. First, pyramid representation creates multiresolution images using a wavelet transform. Second, image segmentation segments the lowest-resolution image of the pyramid using a watershed segmentation algorithm. Third, region merging merges the segmented regions using the third-order moment values of the wavelet coefficients. Finally, the segmented low-resolution image with label is projected into a full-resolution image (original image) by inverse wavelet transform. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as reduce over-segmentation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.287-287
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• 2000

As a method to control the bacteria number in adequate level, a real time control system based on microscope image processing measurement for the bacteria is adopted. For the experiment, Ammonia-oxidizing bacteria such as Acinetobacter sp. are used. This paper proposed hybrid method combined watershed algorithm with adaptive automatic thresholding method to enhance segmentation efficiency of overlapped image. Experiments was done to show the effectiveness of the proposed method compared to traditional Otsu's method, Otsu's method with adaptive automatic thresholding method and human visual method.

• Journal of Environmental Science International
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• v.12 no.10
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• pp.1109-1116
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• 2003

The genetic algorithm is investigated fer parameters estimation of SED (storage - effective drainage) model from the Wi-stream watershed in Nakdong river basin. In the practical application of model, as a number of watershed parameters do not measure directly, it is desirable to make a good estimation from the known rainfall and runoff data. For the estimation of parameters of the SED model using the genetic algorithm, parameters of Green-Ampt equation(SM, K$\_$s/) for the estimation of an effective rainfall and initial storage(y$\_$in/) used in SED model are obtained a regression equation with 5, 10, 20 days antecedent precipitation. And as a consequence of computation, the parameters were obtained to satisfy the proposed objective function. From the comparison of observed and computed hydrographs, it shows a good agreement in the shape and the rising limb, peak, falling limb of hydrograph, so the SED model using the genetic algorithm shows a suitable model for runoff analysis in river basin.