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Topic: Segmentation image processing

Related Topics

Digital image processing

Image processing

Thresholding (image processing)

Image compression

Hough transform

Noise reduction

Feature extraction

Optical flow

Transform coding

Edge detection

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	Image segment - Wikipedia, the free encyclopedia
		In computer vision segmentation of an image is the division of a given (digital) image into contiguous regions.
		In current computer vision algorithms the similarity of image parts is usually defined in terms of color and texture.
		The goal to automatically segment images into semantically meaningful parts is very difficult to achieve.
	en.wikipedia.org /wiki/Image_segment (78 words)

	Segmentation (image processing) - Wikipedia, the free encyclopedia
		In image analysis, segmentation is the partition of a digital image into multiple regions (sets of pixels), according to some criterion.
		Some other segmentation algorithms are based on segmenting images into regions of similar texture according to wavelet or Fourier transforms.
		A segmentation consists of a set of non-overlapping connected regions (the union of which is the image), each of which is smooth and each of which has a piecewise smooth boundary.
	en.wikipedia.org /wiki/Segmentation_(image_processing) (276 words)

	[This is a sample article (Site not responding. Last check: 2007-10-29)
		Image processing is distinguished from computer graphics in its predominant emphasis on images originally produced by cameras and in a goal of analysis rather than synthesis of images.
		Some image processing maps image data to an equivalent transform space in which certain processing is easier.
		Matched stereo pairs of images (images of the same scene taken by two cameras a short distance apart) can be used to infer three-dimensional shape by iterative match-optimization ("relaxation") methods that match their pixels.
	www.cs.nps.navy.mil /people/faculty/rowe/imageprocover.htm (1949 words)

	Fuzzy Image Processing: Fuzzy Image Segmentation
		The different theoretical components of fuzzy image processing provide us with diverse possibilities for development of new segmentation techniques.
		Fuzzy clustering is the oldest fuzzy approach to image segmentation.
		If we interpret the image features as linguistic variables, then we can use fuzzy if-then rules to segment the image into different regions.
	pami.uwaterloo.ca /tizhoosh/segment.htm (358 words)

	Feature Indexing in a Database of Digitized X-rays
		This indexing requires the segmentation of the image contents, identification of relevant anatomy in the segmented images, and classification of the identified anatomy into categories by which the image contents may be indexed.
		We approach this segmentation as a hierarchical procedure with the distinctive regions of the image, including the general spine region, first being segmented at a gross level of detail, followed by a finer level segmentation of the spine region into individual vertebrae.
		The presence of AO in the images becomes noticeable in the cropped spine regions shown in Figure 7, where the Grade 2 and Grade 3 deformity in shape of the vertebrae at the bottom anterior corner is especially visible.
	archive.nlm.nih.gov /pubs/long/ei2001/ei2001.php (4996 words)

	Processing
		Central processing unit The central processing unit (CPU) is the part of a registers is included to hold operands and in...
		Microscope image processing Microscope image processing is a broad term that covers the use of microscope.
		Signal processing Signal processing is the processing, amplification and interpretation of signals.
	www.brainyencyclopedia.com /topics/processing.html (704 words)

	(WO 01/26050) IMPROVED IMAGE SEGMENTATION PROCESSING BY USER-GUIDED IMAGE PROCESSING TECHNIQUES (Site not responding. Last check: 2007-10-29)
		Machine image segmentation processing is constrained to a region of interest indicated by the operator using the drawing tool.
		Automatic segmentation is also applied to each image in a video clip based on a region of interest indicated by the operator on a first image of the clip.
		The region of interest is repositioned from image to image on the basis of detected motion of the object indicated by the region of interest.
	www.wipo.int /ipdl/IPDL-CIMAGES/view/pct/getbykey5?KEY=01/26050.010412 (255 words)

	Image processing
		first we smooth fl and white version of the image (to reduce the blocking nature of the original image) and then choose region of interest (inside the cell) using histogram for thresholding.
		After some morphological operations (follow the titles) to eliminate the background artifacts, we reached to final segmentation which is obviously better the the first approach.
		Rest of the process is similar to the previous ones.
	www.ece.umn.edu /users/baharank/image_hw3.htm (491 words)

	[No title]
		This course, Digital Image Processing, gives a comprehensive treatment of all the important aspects of this topic, including all fundamental steps in digital image processing (image acquisition, enhancement, restoration, wavelets, compression, morphological and color image processing, segmentation, recognition).
		Digital iamage processing is referred to processing digital images (which can be defined as a two-dimensional function, f(x,y), where x and y are spacial (plane) coordinates, and the function f is the itensity or gray level of the image) by means of a digital computer.
		A graduate student is expected to learn in this course basic image formation, to be able to model and analyze image operations, to utilize techniques from spacial and frequency damains, to address both enginereering issues and computational issues, and to get some expereince with image processing and its presentation.
	www.cs.wpi.edu /~dobrush/cs545/f03/intro.html (186 words)

	[No title] (Site not responding. Last check: 2007-10-29)
		An important problem in image processing is the segmentation-partition of an image representing a real scene in regions with sharp boundaries.
		The unknowns are the segmented image, and a set of curves, representing the edges in the image.
		First I will introduce an active contour model "without edges", based segmentation and level sets, having some advantages, compared with classical models: it detects objects whose boundaries are not necessarily defined by gradient, as well as interior contours automatically.
	www.ipam.ucla.edu /abstract.aspx?tid=5154 (273 words)

	The Image Sequence Processing Group
		The objective of the Image Sequence Processing Group is to utilize knowledge of the human visual system to develop and explore both models which can serve as the basis for image and image sequence processing and coding techniques, and the techniques themselves.
		When applying these approaches to image sequences, it is useful to view the sequence as a spatiotemporal volume of data (as shown above), with motion reflected in the structure of the volume.
		Novel image and video processing techniques (including a large class of space- and spatiotemporally-variant filtering methods) are also made possible when using these representations.
	www-ee.eng.hawaii.edu /~treed/ispg (521 words)

	Computer Vision Source Code
		Segmentation results from twenty randomly selected images show an average error that is about the same as that obtained by four experts manually segmenting the images.
		Able Image Analyser supports image analysis functions that include dimensional, gray scale and 24 bits color measurements: distance, area, angle, point, line, pixel profile, histogram etc. (from images or selections) with statistics that calculate basic statistics (count, mean, median, minimum, maximum, range, variance, standard deviation, coefficient of variation, skew and kurtosis) and frequencies.
		Image processing and analysis in Java - ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh.
	www-2.cs.cmu.edu /afs/cs/project/cil/ftp/html/v-source.html (9824 words)

	Detecting a Cell Using Image Segmentation (Image Processing Toolbox Morphology Demos) (Site not responding. Last check: 2007-10-29)
		The object to be segmented differs greatly in contrast from the background image.
		The cell of interest has been successfully segmented, but it is not the only object that has been found.
		An alternate method for displaying the segmented object would be to place an outline around the segmented cell.
	www.clemson.edu /cle4_share/CWE/COES0915_CLUG/REFERENCE/matlabr14/toolbox/images/imdemos/html/morph2.html (413 words)

	3D-DOCTOR Features, 3D Medical Imaging, Volume Visualization, 3D Image Processing, Segmentation, MRI, CT, DICOM, 3D ...
		The 3D microscopy image is courtesy of G. Martins and Dr. W.J. Sigurdson, Director, Confocal Microscope and 3-D Imaging Facility, SUNY at Buffalo.
		Images of different modalities can be registered using the 3D image registration function and fused together to create a new fusion image.
		Other image processing functions include: template-based scanned film cropping, volume resizing, 3D image filtering, Image rotation, orientation adjustment, contrast adjustment, background removal, image combination, linear feature extraction, pattern recognition, segmentation, image mosaic, and color classification can all be performed on your 3D images.
	www.ablesw.com /3d-doctor/3ddoctor.html (519 words)

	Benchmark Electronic Systems - Image Processing Solutions (Site not responding. Last check: 2007-10-29)
		Image Processing today has become an integral part of automation of industrial processes and streams like automobile manufacturing, pharmaceuticals and medicine, medical imaging like CT scans, biology (scanning electron microscopy) forensic study, security applications and remote sensing, etc. It is also an active area of research with multi disciplinary applications.
		Benchmark Image Processing Laboratories are integrated labs combining state of the art equipment ensuring that users get hands on experience in all aspects of image processing systems.
		Matrox Imaging Technology is used by industry leaders in factory automation, process control, electronic and pharmaceutical packaging, semiconductor inspection, robotics, radiology, microscopy, and video surveillance.
	www.benchmark-electronics.com /Products/ipmain.html (975 words)

	Image Segmentation Using Multiresolution Fourier Transform - Li, Wilson (ResearchIndex) (Site not responding. Last check: 2007-10-29)
		Abstract: In this report, the Multiresolution Fourier Transform (MFT) is utilised as an approach to the segmentation of images based on the analysis of local properties in the spatial frequency domain.
		Six major steps are adopted to implement the segmentation of images in this work.
		Firstly, The Laplacian Pyramid method is used as the filter to create the high-pass filtered image.
	citeseer.ist.psu.edu /li95image.html (413 words)

	Image Processing Tool Kit (Site not responding. Last check: 2007-10-29)
		The Image Processing Tool Kit is an extensive collection of image processing and analysis functions which are distributed on a CD-ROM.
		The CD-ROM is intended to be a companion to the "Image Processing Handbook", 2nd Edition by John C. Russ, 1994, CRC Press, Boca Raton, FL, ISBN 0-8493-2516-1.
		Rank operators are nonlinear image processing filters that rank the pixels in a neighborhood in brightness order and then keep the brightest, darkest or median value for the central pixel.
	ddsdx.uthscsa.edu /dig/ipt.html (519 words)

	Amazon.com: Digital Image Processing Using MATLAB: Books: Rafael C. Gonzalez,Richard E. Woods,Steven L. Eddins (Site not responding. Last check: 2007-10-29)
		This is the first book that provides a balanced treatment of image processing basics and software principles used in the practical application of image processing.
		Digital Image Processing Using MATLAB is the first book that provides a balanced treatment of image processing fundamentals and the software principles used in their practical implementation.
		This is important in image processing, where there is a need for extensive experimental work in order to arrive at acceptable problem solutions.
	www.amazon.com /exec/obidos/tg/detail/-/0130085197?v=glance (1127 words)

	CUJ > Image Processing, Part 10: Segmentation Using Edges and Gray Shades (Site not responding. Last check: 2007-10-29)
		This is the tenth in a series of articles on images and image processing.
		There are powerful segmentation techniques that use the edges in an image, grow regions using the gray shades in an image, and use both the edges and gray shades.
		These techniques work well over a range of images because edges and gray shades are important clues to objects in a scene.
	www.cuj.com /documents/s=8129/cuj9306phillips/phillips.htm (690 words)

	Research (Site not responding. Last check: 2007-10-29)
		The contour of reference may be defined by an operator for interactive image segmentation, or it can be deduced from a previous segmentation in video segmentation and tracking.
		For most segmentation applications, the assumption of a parametric deformation is too restrictive.
		The third frame shows the result of the segmentation using both the shape prior and the homogeneity properties.
	www.i3s.unice.fr /~gastaud/shape_prior.html (518 words)

	Image processing, image matlab processing using, image processing tool (Site not responding. Last check: 2007-10-29)
		PEIPA is an archive relating to image processing and analysis, with emphasis on computer vision.
		The IEEE International Conference on Image Processing (ICIP) is widely regarded as the most prestigious forum for the presentation of technological advances...
		Graphical Models is devoted to the synergy between computer graphics, computer vision, and image processing in the areas of model acquisition,...
	www.lookfinance.com /image-processing.html (1205 words)

	Vision Research Lab - Publications
		An image segmentation criterion is proposed that groups similar pixels together to form regions.
		Abstract preview: "An image segmentation scheme that utilizes image-based flow fields in a curve evolution framework is presented.
		Abstract preview: "Image registration is the process of matching two images so that corresponding coordinate points in the two images correspond to the same physical region of the scene being imaged.
	vision.ece.ucsb.edu /publications (7009 words)

	Digital Image Processing
		In many business and industry application domains handling and processing of digital images is a basic and important component.
		This course prepares students in the fundamentals of digital image processing as used in various applications as outlined above and illustrates the various effects one can achieve with digital images and how to extract fundamental information.
		Use the flower image of Assignment 1 for edge detection and this Image Gallery for contrast enhancement.
	www.ics.uci.edu /~majumder/DIP/dip.htm (222 words)

	Digital Image Processing: Color Image Segmentation -- from Mathematica Information Center
		Digital Image Processing allows you to manipulate color images as conveniently and easily as monochrome images.
		Color images may be represented in three different color formats and two different color interleaving methods, allowing you to select the most appropriate format for any color processing application.
		We use amplitude thresholding and masking to segment an example image according to color features.
	library.wolfram.com /infocenter/Demos/401 (125 words)

	ITK - Image and Signal Processing - Research - Scientific Computing and Imaging Institute
		The Insight Toolkit (ITK) is an open source, freely available, object-oriented software package for medical image processing, segmentation, and registration.
		The Insight Software Consortium has met its primary goals for the creation of an archival vehicle for image processing algorithms and an established functioning platform to accelerate new research efforts.
		The Insight Toolkit project is emerging as a clear success and a significant and permanent contribution to the field of medical imaging.
	www.sci.utah.edu /research/itk.html (358 words)

	efg's Image Processing Page
		Russ, John C., The Image Processing Handbook (Third Edition), CRC Press, 1999.
		S.J. Sangwine and R.E.N. Horne (editors), The Colour Image Processing Handbook, Chapman and Hill, 1998.
		The ongoing mission of this organization is to continue to enhance the standard to accommodate future technologies.
	www.efg2.com /Lab/Library/ImageProcessing (540 words)

	PEER GROUP PROCESSING FOR IMAGE SEGMENTATION (Site not responding. Last check: 2007-10-29)
		BACKGROUND: Edge or boundary detection and image segmentation often constitute a crucial initial step before performing high-level tasks such as object recognition and scene interpretation.
		While the algorithm should strengthen the edges of important features without changing their location, it should also smooth the region interiors and reduce undesirable edges associated with clutter and noise.
		Parameters are directly related to the image objects to be enhanced, while, for most techniques, the method of parameter selection is unclear.
	research.ucsb.edu /policy/tech/1997-158__Peer_Group_Processing_for_Image_Segmentation_files/1997-158__Peer_Group_Processing_for_Image_Segmentation.htm (149 words)

	A background based adaptive page segmentation algorithm (Site not responding. Last check: 2007-10-29)
		Based on the extraction of the background, it offers the benefit of being adaptive to the context of the document and to be insensitive to the orientation of the text blocks.
		Another advantage of the proposed method is that a hierarchical segmentation can be derived from the image built upon the octagonal pattern.
		The algorithms are based on an input-time tracing principle and use a single scan of the image, they are very well suited to a real-time implementation.
	csdl2.computer.org /persagen/DLAbsToc.jsp?resourcePath=/dl/proceedings/&toc=comp/proceedings/icdar/1995/7128/01/7128toc.xml&DOI=10.1109/ICDAR.1995.598961 (269 words)

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