• Title/Summary/Keyword: curve segmentation

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AN IMAGE SEGMENTATION LEVEL SET METHOD FOR BUILDING DETECTION

  • Konstantinos, Karantzalos;Demetre, Argialas
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.610-614
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    • 2006
  • In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

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Automatic Bone Segmentation from CT Images Using Chan-Vese Multiphase Active Contour

  • Truc, P.T.H.;Kim, T.S.;Kim, Y.H.;Ahn, Y.B.;Lee, Y.K.;Lee, S.Y.
    • Journal of Biomedical Engineering Research
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    • v.28 no.6
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    • pp.713-720
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    • 2007
  • In image-guided surgery, automatic bone segmentation of Computed Tomography (CT) images is an important but challenging step. Previous attempts include intensity-, edge-, region-, and deformable curve-based approaches [1], but none claims fully satisfactory performance. Although active contour (AC) techniques possess many excellent characteristics, their applications in CT image segmentation have not worthily exploited yet. In this study, we have evaluated the automaticity and performance of the model of Chan-Vese Multiphase AC Without Edges towards knee bone segmentation from CT images. This model is suitable because it is initialization-insensitive and topology-adaptive. Its segmentation results have been qualitatively compared with those from four other widely used AC models: namely Gradient Vector Flow (GVF) AC, Geometric AC, Geodesic AC, and GVF Fast Geometric AC. To quantitatively evaluate its performance, the results from a commercial software and a medical expert have been used. The evaluation results show that the Chan-Vese model provides superior performance with least user interaction, proving its suitability for automatic bone segmentation from CT images.

Voronoi 도형을 이용한 자유곡선의 옵셋팅

  • 정재훈;김광수
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.713-718
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    • 1994
  • Voronoi diagrams for closed shapes have many practical applications, ranging from numerical control machining to mesh generation. Shape offset based on Voronoi diagram avoids the topological problems encountered in traditional offsetting algorithms. In this paper, we propose a procedure for generating a Voronoi diagram and an exact offset for planar curve. A planer curve can be defined by free-form curve segements. The procedure consists of three steps : 1) segmentation by minimum curvature, 2) construction of Voronoi diagram, and 2) generation of the exact offset.

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AUTOMATIC DETECTION OF OIL SPILLS WITH LEVEL SET SEGMENTATION TECHNIQUE FROM REMOTELY SENSED IMAGERY

  • Konstantinos, Karantzalos;Demetre, Argialas
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.126-129
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    • 2006
  • The marine environment is under considerable threat from intentional or accidental oil spills, ballast water discharged, dredging and infilling for coastal development, and uncontrolled sewage and industrial wastewater discharges. Monitoring spills and illegal oil discharges is an important component in ensuring compliance with marine protection legislation and general protection of the coastal environments. For the monitoring task an image processing system is needed that can efficiently perform the detection and the tracking of oil spills and in this direction a significant amount of research work has taken place mainly with the use of radar (SAR) remote sensing data. In this paper the level set image segmentation technique was tested for the detection of oil spills. Level set allow the evolving curve to change topology (break and merge) and therefore boundaries of particularly intricate shapes can be extracted. Experimental results demonstrated that the level set segmentation can be used for the efficient detection and monitoring of oil spills, since the method coped with abrupt shape’s deformations and splits.

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Surface Segmentation and Feature Description using the Signature Technique (Signature 기법을 이용한 면의 특징 표현 및 분할 기법)

  • 이보형;한헌수
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.12
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    • pp.90-97
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    • 1997
  • This paper presents a new algorithm for surface segmentation and feature description. The algorithm extracts the signature of an edge image based on the signature technqique[12] in the first stage. If there exists a range in the angle axis where more than two signatures form a closed curve, we can conclude there is a surface inside the range. Using this feature of the signature, surfaces can be segmented. The surface features such as number of vertices, number of edges, and type of surfaces can also be extracted by finding the signatures of individual surfaces. This algorithm has distinguished advantages: it can easily recover the lost part occuring in the edge iage using the curve fitting method and it can extract surface features even when surfaces are rotated in 3-D space.

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A Study on the Edge Construction of CMM Data Using a Method of Mean Curvature Block (평균곡률 구간법을 이용한 CMM 데이터의 경계 형성 연구)

  • Chang, Byoung-Chun;Kim, Dae-Il;Oh, Seok-Hyung
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.9 no.1
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    • pp.74-80
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    • 2010
  • The purpose of reverse engineering design using 3D measurement data is an accurate reconstruction of real body. In oder to accomplish this object, it is important that creating exact extracting edges should be studying out first of all. This study used edge-based method to find out edge point from the measuring point data. The characteristics are analysed using the mean curvature block method on the fitting NURBS curve and defined edges through block removal condition. The results showed that only using the NURBS curve of maximum curvature analysis to define correct edge of real geometry is limited, but this segmentation approach provides simplified necessary condition for edge classification, and an effectiveness to classify a straight line, curves and fillets etc.

FINE SEGMENTATION USING GEOMETRIC ATTRACTION-DRIVEN FLOW AND EDGE-REGIONS

  • Hahn, Joo-Young;Lee, Chang-Ock
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.11 no.2
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    • pp.41-47
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    • 2007
  • A fine segmentation algorithm is proposed for extracting objects in an image, which have both weak boundaries and highly non-convex shapes. The image has simple background colors or simple object colors. Two concepts, geometric attraction-driven flow (GADF) and edge-regions are combined to detect boundaries of objects in a sub-pixel resolution. The main strategy to segment the boundaries is to construct initial curves close to objects by using edge-regions and then to make a curve evolution in GADF. Since the initial curves are close to objects regardless of shapes, highly non-convex shapes are easily detected and dependence on initial curves in boundary-based segmentation algorithms is naturally removed. Weak boundaries are also detected because the orientation of GADF is obtained regardless of the strength of boundaries. For a fine segmentation, we additionally propose a local region competition algorithm to detect perceptible boundaries which are used for the extraction of objects without visual loss of detailed shapes. We have successfully accomplished the fine segmentation of objects from images taken in the studio and aphids from images of soybean leaves.

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Data Structure Extraction of Boundary Segments by Region Labeling (영역 라벨링에 의한 경계선 세그먼트의 데이터 구조 추출)

  • 최환언;정광웅;김두영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.1
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    • pp.80-89
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    • 1992
  • This paper presents algorithms which are region labeling and data structure of a boundary segmentation as image intermediate description process. In the method, the algorithms are region labeling, boundary segmentation, line and curve fitting and extracting data structure of each segment. As a result, a data structure of image is described by a set of region number, segment number, line or curve, starting point and end point of each segment and coefficient of line or curve. These data structures would serve for higher level processing as object recognition. For example we will use this data structure to solve the correspondence problem of stereoscopic image information. And we verified these algorithms through the image reconstruction of data structure.

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Iris Segmentation and Recognition

  • Kim, Jae-Min;Cho, Seong-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.3
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    • pp.227-230
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    • 2002
  • A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

Segmentation of Digital Curves by Structural Analysis (구조해석에 의한 디지털 곡선의 분리)

  • 류승필;권오석;김태균
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.12
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    • pp.1984-1994
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    • 1989
  • Techniques for approximating digitalcurves by polygonal lines are a valuable tool for image analysis and data compression. S. Shilien proposed a method for segmenting a digital curve into digital straight line segments digital straight line segments which are not satisfied with the structural properties, and have more than one break point by Shilien's method. Here, the structural representation of digital straight lines and digital staight line segments is described. And a method for segmenting a digital curve into digital straight line segments which are not satisfied with the structural properties, and have more than one break point by Shilien's method. Here, the structural representation of digital straight lines and digital staight line segments is described. And a method for segmenting a digital curve into digital straight line segments which may be not satisfied with the structural properties is proposed. The number of break points extracted by this method is less than that by S. Shilien's method from the digital curve which includes the digital straight line segments not satisfied with the structural properties.

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