• JSTS:Journal of Semiconductor Technology and Science
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• 제12권2호
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• pp.175-185
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• 2012

Predictive watershed transform is a popular object segmentation algorithm which achieves a speed-up by identifying image regions that are different from the previous frame and performing object segmentation only for those regions. However, incorrect segmentation is often generated by the predictive watershed transform which uses only local information in merge-split decision on boundary regions. This paper improves the predictive watershed transform to increase the accuracy of segmentation results by using the additional information about the root of boundary regions. Furthermore, the proposed algorithm is processed in a block-based manner such that an image frame is decomposed into blocks and each block is processed independently of the other blocks. The block-based approach makes it easy to implement the algorithm in hardware and also permits an extension for parallel execution. Experimental results show that the proposed watershed transform produces more accurate segmentation results than the predictive watershed transform.

• 대한전자공학회논문지SP
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• 제40권2호
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• pp.1-10
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• 2003

Watershed 알고리즘은 형태학 분야에서 연구되어 온 것으로 단순화된 영상에 대한 경사 영상 화소의 밝기 값을 고도로 생각함으로써 영상을 분할하는데 많이 적용하였다. 하지만, 노이즈에 의해 훼손된 영상을 분할 할 경우, 수 많은 local minima로 인해 영상이 과 분할되고, 분할된 영역을 병합하기 위한 계산 시간 증가의 문제점이 발생된다. 이러한 문제점을 해결하기 위해, 본 논문에서는 웨이블릿 변환을 사용한 watershed 기반 영상 분할의 효율성 증대를 위한 방법을 제안한다. 제안한 영상 분할 방법은 웨이블릿 변환을 이용한 영상의 계층적 표현인 피라미드 표현 단계, watershed 알고리즘을 이용한 영상 분할 단계, 웨이블릿 계수(coefficient)를 이용한 영역 병합 단계와 웨이블릿 역 변환(inverse wavelet transform)을 이용한 영역 투영 단계고 구성된다. 제안된 방법은 노이즈가 포함된 훼손된 영상을 분할 시 발생하는 과 분할문제를 감소시킬 뿐만 아니라, 분할 성능의 개선됨을 알 수 있다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (2)
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• pp.472-474
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• 2001

본 논문은 wavelet 기반의 watershed를 이용한 효율적인 영상 분할을 기법을 제안한다. 영상 분할을 위해 입력 영상을 wavelet transform을 사용하여 low-resolution 영상을 생성한 후 watershed 알고리즘을 이용해 분할하고, 이를 Inverse wavelet transform함으로써 원 영상으로 복원한다. 복원된 영상을 의미 있는 영역들로 분할하기 위해 wavelet 특징값의 유사성을 두 인접한 영역에 비교하여 병합한다. 실험 결과 제안한 방법은 영상의 잡음에 대한 강인함과 영상의 과분할 문제를 해결할 수 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.53-56
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• 2002

In this paper, we propose the method of iris lacuna extraction using watershed transform. Lacuna is salient feature of iris. It has three dimensional structure formed by leak of pigmentation and loss of fiber tissues. Lacuna can be used for iris recognition system, and generally used in health diagnosis and character analysis with its shape and position. The main idea of the proposed method is applying the watershed transform to radial gray scale profile of iris image. The result shows that the lacuna can be extracted automatically from eye image.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.482-485
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• 2000

A modified watershed transform is proposed which is context-free marker-controlled and minima imposition-free to reduce the over-segmentation and to speedup the transform. In contrast to the conventional methods in which a priori knowledge, such as flat zones, zones of homogeneous texture, and morphological distance, is required for marker extraction, context-free marker extraction is proposed by using the attention operator based on the GST (generalized symmetry transform). By using the context-free marker, the proposed watershed transform exploit marker-constrained labeling to speedup the computation and to reduce the over-segmentation by eliminating the unnecessary geodesic reconstruction such as the minima imposition and thereby eliminating the necessity of the post-processing of region merging. The simulation results show that the proposed method can extract context-free markers inside the objects from the complex background that includes multiple objects and efficiently reduces over-segmentation and computation time.

• 융합신호처리학회논문지
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• 제12권2호
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• pp.91-95
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• 2011

In this paper, we present an improved multi-scale gradient algorithm. The proposed algorithm works the effectively handling of both step and blurred edges. In the proposed algorithm, the image sharpening operator is sharpening the edges and contours of the objects. This operation gives an opportunity to get noise reduced image and step edged image. After that, multi-scale gradient operator works on noise reduced image in order to get a gradient image. The gradient image is segmented by watershed transform. The approach of region merging is used after watershed transform. The region merging is carried out according to the region area and region homogeneity. The region number of the proposed algorithm is 36% shorter than that of the existing algorithm because the proposed algorithm produces a few irrelevant regions. Moreover, the computational time of the proposed algorithm is relatively fast in comparison with the existing one.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.192-194
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• 2003

Since the details in quasi-homogeneous region will be destroyed from the conventional global image enhancement method such as histogram equalization. This defect is caused by the saturation of gray level in equalization process. So the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the region itself. To obtain the quasi- homogeneous regions, the original image must be segmented. Here we applied the watershed transform to the interesting image. Since the watershed transform is based on mathematical morphology, therefore, the regions touch can be effectively separated. Hence two adjacent regions which have the similar gray pixels will be split off. The process will be independently applied to three different spectral images. Then three different colors are assigned to each processed image in order to produce a color composite image. By the proposed algorithm, the result image shows the better perception on image details. Therefore, the high efficiency of image classification can be obtained by using this color image.

• 대한전자공학회논문지SP
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• 제38권3호
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• pp.237-246
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• 2001

본 논문에서는 복잡 배경으로부터 임의의 다중물체를 효과적으로 검출함과 동시에 고속 분할할 수 있는 문맥자유 마커제어 분수계 변환 (context-free marker controlled watershed transform)을 제안하였다. 먼저 잡음에 강건한 주목 연산자 (attention operator)를 써서 복잡 배경 속의 여러 물체 별로 그 위치를 검출하여 문맥자유 마커를 추출하고, 이를 마커로 한정된 레이블링 (marker constrained labeling)을 하여 최소값 부과과정이 필요 없는 문맥자유 마커제어 분수계 변환을 제안함으로써 과분할없이 신속하게 분할할 수 있도록 하였다. 다중 물체가 포함된 복잡 영상에 적용 실험하여, 대상 물체에 대한 사전정보 없이도 과분할과 처리시간을 대폭 줄여 효과적으로 다중 물체를 검출함과 동시에 고속 분할이 가능함을 확인 할 수 있었다.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.

• 한국전자통신학회논문지
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• 제5권3호
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• pp.309-314
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• 2010

본 논문에서는 인터넷상에서의 지능형 감시 카메라 시스템(Intelligent Security Camera: ISC)을 제안한다. ISC 방법은 워터쉐드 알고리즘에 기반하여 카메라에 입력된 영상을 분할하는 단계와 skin-color model을 사용하여 얼굴의 후보지역을 탐지하는 단계, 그리고 마지막으로 SVM(Support Vector Machine)을 사용하여 얼굴 후보영역에서 얼굴을 검증하는 단계로 구성되어 있다. Skin-color Model을 이용하여 찾아진 얼굴후보 영역으로부터 웨이블렛 변환계수들을 추출한다. 웨이블렛 변환계수들을 SVM의 입력으로 하여 실제 얼굴영역을 검증한다. SVM의 입력으로 실험결과에서 제안된 방법이 감시시스템, 화상회의 시스템과 같은 얼굴을 인식 추적하는 시스템에 적용될 수 있음을 보인다.