• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.481-490
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• 2002

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic information has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing for off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods that effectively extracts skeleton through conditional test mask considering routing time and quality of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1023-1032
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• 2003

Object-based coding, such as MPEG-4, enables various content-based functionalities for multimedia applications. In order to support such functionalities, as well as to improve coding efficiency, each frame of video sequences should be segmented into video objects. In this paper. we propose an effective video object segmentation method using nonlinear multiscale filtering and spatio-temporal information. Proposed method performs a spatial segmentation using a nonlinear multiscale filtering based on the stabilized inverse diffusion equation(SIDE). And, the segmented regions are merged using region adjacency graph(RAG). In this paper, we use a statistical significance test and a time-variant memory as temporal segmentation methods. By combining of extracted spatial and temporal segmentations, we can segment the video objects effectively. Proposed method is more robust to noise than the existing watershed algorithm. Experimental result shows that the proposed method improves a boundary accuracy ratio by 43% on "Akiyo" and by 29% on "Claire" than A. Neri's Method does.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1067-1087
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• 2018

In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top area automatically due to outliers and large holes of point cloud. Thus, we propose a technique to extract building boundary semi-automatically from the DSM created from stereo images. The technique consists of watershed segmentation for using user input as markers and recursive MBR algorithm. Since the proposed method only inputs simple marker information that represents building areas within the DSM, it can create building boundary efficiently by minimizing user input.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.763-765
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• 2004

현재 의료 영상을 이용한 신속하고 정확한 진단과 치료를 위하여 각 기관별로 영상을 분할하는 방식이 기본적으로 사용되고 있다. 본 논문에서는 워터쉐드(Watershed) 알고리즘을 이용하여 해부학적 기관 중 폐 영역을 분할하는 방식을 제안한다. 초기에 소벨 에지 마스크(Sobel Edge Mask)를 이용하여 윤곽선을 강조하여 워터쉐드 알고리즘을 적용하였을 경우 과다 분할되는 문제점이 발생한다. 이를 해결하기 위하여 제거(Opening) 연산과 채움(Closing) 연산을 이용하여 마커(Marker) 정보를 추출하여 워터쉐드 알고리즘을 재적용하여 폐 영역 이미지를 분할하였다. 본 논문에서 제안한 마커 정보를 이용한 워터쉐드 재적용 방식은 폐 영역 효율적이고 정확하게 추출한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.637-640
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• 2002

본 연구에서는 Watershed변환을 이용하여 영상을 분할할 때 과분할되는 문제점을 해결하기 위하여 영상의 경계를 강화하고 작은 지역 최소들을 효과적 제거하는 방법을 제안한다. 제안된 방법은 영상속의 양자화와 노이즈에 의한 에러를 제거하는 영상필터링 단계와 제안된 방법에 의해 CERM변환을 수행하는 영상재구성단계 그리고 Watershed변환을 수행하여 영상을 분할하는 단계로 구성되어 있다. 제안된 방법으로 영상을 분할해본 결과 과분할을 효과적으로 줄일 수 있었다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1136-1142
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• 2010

In this study, an efficient removal algorithm for specular reflections in a tooth color image is proposed to minimize the artefact interrupting color image segmentation. The pixel values of RGB color channels are initially reversed to emphasize the features in reflective regions, and then those regions are automatically detected by utilizing perceptron artificial neural network model and those prominent intensities are corrected by applying a smoothing spatial filter. After correcting specular reflection regions, multiple seeds in the tooth candidates are selected to find the regional minima and MCWA(Marker-Controlled Watershed Algorithm) is applied to delineate the individual tooth region in a CCD tooth color image. Therefore, the accuracy in segmentation for separating tooth regions can be drastically improved with removing specular reflections due to the illumination effect.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.735-740
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• 2005

Video segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries, But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes that adaptive trimmed mean filter for resolving the over segmentation of image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.38-49
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• 1996

In this paper, we propose a fast hierarchical image segmentation using mathematical morphology. The proposed segmentation method is composed of five basic steps; multi-thresholding, open-close by reconstructing, mode operation, marker extraction, and region decision. In the multi-thresholding, an input image is simplified by Lloyd clustering algorithm. The multi-thresholded image then is more simplified by open-close by reconstruction and mode operating. In the region decision, to which region each uncertainty pixel belongs finally is decided by a watershed algorithm. Experimental results show that the quality of the segmentation results by the proposed method is not inferior to that by the conventional method and the average times elapsed by the proposed method can be reduced by one tghird of those elapsed by the conventional method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.42-47
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• 2007

Video Segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries. But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes that adaptive trimmed mean filter for resolving the over segmentation of image. Simulation result, we confirm that proposed ATM filter improves the performance to remove noise and reduces damage for the clear degree of image in case of the noise ratio of 20% and over.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.63-71
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• 2003

This paper describes a color image segmentation algorithm based on region merging using hue difference as a restrictive condition. The proposed algorithm using mathematical morphology and a modified watershed algorithm does over-segmentation in the RGB space to preserve contour information of regions. Then, the segmentation result of color image is acquired by repeated region merging using hue differences as a restrictive condition. This stems from human visual system based on hue, saturation, and intensity. Hue difference between two regions is used as a restrictive condition for region merging because it becomes more important factor than color difference if intensity is not low. Simulation results show that the proposed color image segmentation algorithm provides efficient segmentation results with the predefined number of regions for various color images.