1 Unsupervised Segmentation of Predefined Shapes in Multivariate Images

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1 Unsupervised Segmentation of Predefined Shapes in Multivariate Images (2003)

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by J. C. Noordam , L. M. C. Buydens

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2068	Pattern Recognition with Fuzzy Objective Function Algorithms - Bezdek - 1981 (Show Context) Citation Context ...and less spurious pixels. keywords: Fuzzy C-means clustering, spectral-spatial clustering, multivariate imaging, segmentation 1 Introduction The use of the unsupervised Fuzzy C-Means (FCM) clustering =-=[1]-=- to segment a multivariate image in meaningful regions has been a research topic for many decades [2, 3, 4, 5, 6, 7]. The main reason for the popularity of FCM as an image segmentation technique is it...
197	An adaptive clustering algorithm for image segmentation - Pappas - 1992 (Show Context) Citation Context ...ed by this approach. Therefore, several other ideas have been presented in literature which all try to use spatial information during the clustering process by modifying the objective function of FCM =-=[7, 11, 12, 13, 14, 15]-=-. In some modifications the idea is to use FCM as an image compression tool and therefore the focus of the algorithm is on keeping the original image characteristics and remove the unimportant details...
170	Review of MR image segmentation techniques using pattern recognition, - BEZDEK, HALL, et al. - 1993 (Show Context) Citation Context ...ases where only few multivariate images with no a priori (e.g. spectral) information are available and no training set can be extracted from these multivariate images to train a supervised classifier =-=[8, 4]-=-. Such images are produced by Magnetic Resonance Imaging (MRI) devices and multispectral cameras in fruit and vegetable inspection. Multispectral images reveal information about the spectral propertie...
106	A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain. - Hall, Bensaid, et al. - 1992 (Show Context) Citation Context ...te imaging, segmentation 1 Introduction The use of the unsupervised Fuzzy C-Means (FCM) clustering [1] to segment a multivariate image in meaningful regions has been a research topic for many decades =-=[2, 3, 4, 5, 6, 7]-=-. The main reason for the popularity of FCM as an image segmentation technique is its transparency and unsupervised nature. FCM is especially applied as segmentation technique in cases where only few ...
66	Fuzzy Clustering with Partial Supervision,” - Pedrycz, Walwtzky - 1997 (Show Context) Citation Context ...< uik <N ∀ i (4) i=1 k=1 A detailed description of FCM is described in literature [1]. 2.3 Fuzzy C-Means with auxiliary variable As stated in section 2.1, SG-FCM is based on a modified version of FCM =-=[16]-=- to incorporate a priori spatial information in the clustering process. This modified version of FCM uses an auxiliary variable to add a-priori information (spectral or spatial) to influence the clust...
64	Efficient Implementation of the Fuzzy C-Means Clustering Algorithms. - Cannon, Dave, et al. - 1986 (Show Context) Citation Context ...te imaging, segmentation 1 Introduction The use of the unsupervised Fuzzy C-Means (FCM) clustering [1] to segment a multivariate image in meaningful regions has been a research topic for many decades =-=[2, 3, 4, 5, 6, 7]-=-. The main reason for the popularity of FCM as an image segmentation technique is its transparency and unsupervised nature. FCM is especially applied as segmentation technique in cases where only few ...
49	Princen, 'Comparative study of Hough transform methods for circle finding - Yuen, J - 1990 (Show Context) Citation Context ...ion 2.1, the SG-FCM algorithm can detect and emphasize objects of arbitrary shape during clustering. In this section, a model to detect solid circles of unknown radius is described. A Hough transform =-=[17, 18, 19]-=- is implemented for the circle detection procedure which searches for circular shaped objects in the segmented image. The Hough transform method of shape 8analysis uses a constraint equation relating...
35	Image segmentation by a fuzzy clustering algorithm using adaptive spatially constrained membership functions,” - Tolias, Panas - 1998 (Show Context) Citation Context ...ed by this approach. Therefore, several other ideas have been presented in literature which all try to use spatial information during the clustering process by modifying the objective function of FCM =-=[7, 11, 12, 13, 14, 15]-=-. In some modifications the idea is to use FCM as an image compression tool and therefore the focus of the algorithm is on keeping the original image characteristics and remove the unimportant details...
30	Color Image Segmentation Based on 3-D Clustering: Morphological Approach," - Park, Yun, et al. - 1998 (Show Context) Citation Context ...e spatial information is combined with spectral information to improve segmentation results. The majority of applications use a sequence of both spectrally and spatially based segmentation operations =-=[6, 9, 10]-=-. In these applications, the FCM segmented image is followed by a spatially based filter which tries to correct the segmentation errors. Although in some cases good results are obtained, the spatially...
30	A contiguity-enhanced k-means clustering algorithm for unsupervised multispectral image segmentation - Theiler - 1997 (Show Context) Citation Context ...ed by this approach. Therefore, several other ideas have been presented in literature which all try to use spatial information during the clustering process by modifying the objective function of FCM =-=[7, 11, 12, 13, 14, 15]-=-. In some modifications the idea is to use FCM as an image compression tool and therefore the focus of the algorithm is on keeping the original image characteristics and remove the unimportant details...
27	Fast contour identification through efficient Hough Transform and simplest interpretation strategy - Gerig, Klein - 1986 (Show Context) Citation Context ...ion 2.1, the SG-FCM algorithm can detect and emphasize objects of arbitrary shape during clustering. In this section, a model to detect solid circles of unknown radius is described. A Hough transform =-=[17, 18, 19]-=- is implemented for the circle detection procedure which searches for circular shaped objects in the segmented image. The Hough transform method of shape 8analysis uses a constraint equation relating...
15	Spectral image analysis for measuring ripeness of tomatoes. - Polder, Heijden, et al. - 2002 (Show Context) Citation Context ...olan Jenner) were positioned in front of the line arrays. Detailed information about the used multispectral imaging setup and the spatial and spectral calibration procedure is described in literature =-=[20]-=-. 4.2 Experiment 1: Segmentation of a synthetic image The synthetic image experiment demonstrates the principle of the spatially guided clustering and shows the effect of different noise levels on the...
9	A Cluster Scheme for Multispectral Images - Goldberg, Shlien (Show Context) Citation Context ...te imaging, segmentation 1 Introduction The use of the unsupervised Fuzzy C-Means (FCM) clustering [1] to segment a multivariate image in meaningful regions has been a research topic for many decades =-=[2, 3, 4, 5, 6, 7]-=-. The main reason for the popularity of FCM as an image segmentation technique is its transparency and unsupervised nature. FCM is especially applied as segmentation technique in cases where only few ...
7	Automated detection of the left ventricular region in magnetic resonance images by Fuzzy C-Means model - Boudraa - 1997 (Show Context) Citation Context ...e spatial information is combined with spectral information to improve segmentation results. The majority of applications use a sequence of both spectrally and spatially based segmentation operations =-=[6, 9, 10]-=-. In these applications, the FCM segmented image is followed by a spatially based filter which tries to correct the segmentation errors. Although in some cases good results are obtained, the spatially...
6	Multi-spectral image segmentation algorithm combining spatial and spectral information - Paclik, RPW, et al. - 2001 (Show Context) Citation Context ...ed by this approach. Therefore, several other ideas have been presented in literature which all try to use spatial information during the clustering process by modifying the objective function of FCM =-=[7, 11, 12, 13, 14, 15]-=-. In some modifications the idea is to use FCM as an image compression tool and therefore the focus of the algorithm is on keeping the original image characteristics and remove the unimportant details...
4	A survey of fuzzy clustering. Mathematical and Computer modelling 18 - YANG - 1993 (Show Context) Citation Context ...te imaging, segmentation 1 Introduction The use of the unsupervised Fuzzy C-Means (FCM) clustering [1] to segment a multivariate image in meaningful regions has been a research topic for many decades =-=[2, 3, 4, 5, 6, 7]-=-. The main reason for the popularity of FCM as an image segmentation technique is its transparency and unsupervised nature. FCM is especially applied as segmentation technique in cases where only few ...
4	Spatial-spectral image analysis using classical and neural algorithms - Roberts, Gisler, et al. (Show Context) Citation Context ...ed by this approach. Therefore, several other ideas have been presented in literature which all try to use spatial information during the clustering process by modifying the objective function of FCM =-=[7, 11, 12, 13, 14, 15]-=-. In some modifications the idea is to use FCM as an image compression tool and therefore the focus of the algorithm is on keeping the original image characteristics and remove the unimportant details...
3	den Broek, "Multivariate image segmentation based on geometrically guided fuzzy C-means clustering - Noordam, van - 2002 (Show Context) Citation Context ...te imaging, segmentation 1 Introduction The use of the unsupervised Fuzzy C-Means (FCM) clustering [1] to segment a multivariate image in meaningful regions has been a research topic for many decades =-=[2, 3, 4, 5, 6, 7]-=-. The main reason for the popularity of FCM as an image segmentation technique is its transparency and unsupervised nature. FCM is especially applied as segmentation technique in cases where only few ...
2	A survery of the Hough transforms," Computer graphics and image processing - Illingworth, Kittler - 1988 (Show Context) Citation Context ...ion 2.1, the SG-FCM algorithm can detect and emphasize objects of arbitrary shape during clustering. In this section, a model to detect solid circles of unknown radius is described. A Hough transform =-=[17, 18, 19]-=- is implemented for the circle detection procedure which searches for circular shaped objects in the segmented image. The Hough transform method of shape 8analysis uses a constraint equation relating...