Results 1 - 10 of 1,211

Contour Detection and Hierarchical Image Segmentation

by Pablo Arbeláez, Michael Maire, Charless Fowlkes, Jitendra Malik - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2010
"... This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentati ..."
Abstract - Cited by 389 (24 self) - Add to MetaCart
and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by userspecified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.

Unsupervised Segmentation of Color-Texture Regions in Images and Video

by B. S. Manjunath, Yining Deng, Yining Deng , 2001
"... A new method for unsupervised segmentation of color-texture regions in images and video is presented. This method, which we refer to as JSEG, consists of two independent steps: color quantization and spatial segmentation. In the first step, colors in the image are quantized to several representative ..."
Abstract - Cited by 318 (3 self) - Add to MetaCart
the class-map is proposed. Applying the criterion to local windows in the class-map results in the "Jimage, " in which high and low values correspond to possible boundaries and interiors of colortexture regions. A region growing method is then used to segment the image based on the multiscale J

Object categorization by learned universal visual dictionary

by J. Winn, A. Criminisi, T. Minka - IN ICCV , 2005
"... This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class models are automatically learned from a set of training images. The method is simple and extremely fast, making it suitable ..."
Abstract - Cited by 302 (8 self) - Add to MetaCart
This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class models are automatically learned from a set of training images. The method is simple and extremely fast, making

Segmentation of Medical Images Using Adaptive Region Growing

by Regina Pohle, Klaus D. Toennies , 2001
"... Interaction increases flexibility of segmentation but it leads to undesirable behavior of an algorithm if knowledge being requested is inappropriate. In region growing, this is the case for defining the homogeneity criterion, as its specification depends also on image formation properties that are n ..."
Abstract - Cited by 34 (2 self) - Add to MetaCart
that are not known to the user. We developed a region growing algorithm that learns its homogeneity criterion automatically from characteristics of the region to be segmented. The method is based on a model that describes homogeneity and simple shape properties of the region. Parameters of the homogeneity criterion

Region Growing: A New Approach

by S.A. Hojjatoleslami, J. Kittler - IEEE Transactions on Image Processing , 1995
"... Accurate segmentation of images is one of the most important objectives in image analysis. The two conventional methods of image segmentation, region based segmentation and boundary finding, often suffer from a variety of limitations. Many methods have been proposed to overcome the limitations but t ..."
Abstract - Cited by 82 (1 self) - Add to MetaCart
Accurate segmentation of images is one of the most important objectives in image analysis. The two conventional methods of image segmentation, region based segmentation and boundary finding, often suffer from a variety of limitations. Many methods have been proposed to overcome the limitations

New Methods for Leak Detection and Contour Correction in Seeded Region Growing Segmentation

by T. Heimann, M. Thorn, T. Kunert, H. -p. Meinzer - In 20th ISPRS Congress, Istanbul 2004, International Archives of Photogrammetry and Remote Sensing, vol. XXXV, 317–322, 2004. Rafał H. Kartaszyński et al. / XI Conference "Medical Informatics & Technologies" - 2006 , 2004
"... Segmentation, i.e. the labelling of objects in image data, is a crucial step in many medical imaging processing tasks, e.g. operation planning, radio therapy or diagnostics. Seeded region growing is a basic yet effective method for semi-automatic segmentation. Its major drawback is that poor contras ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
contrast at the organ edges may result in leaks, letting the area grow far beyond the region of interest. We developed a new method to reliably detect the origins of these leak regions and correct the segmentation results. Our approach is based on the observation that leaks are normally characterized by a

Multiresolution Techniques for Interactive Texture-Based Volume Visualization

by Eric LaMar, Bernd Hamann, Kenneth I. Joy , 1999
"... We present a multiresolution technique for interactive texture-based volume visualization of very large data sets. This method uses an adaptive scheme that renders the volume in a region-of-interest at a high resolution and the volume away from this region at progressively lower resolutions. The alg ..."
Abstract - Cited by 147 (8 self) - Add to MetaCart
We present a multiresolution technique for interactive texture-based volume visualization of very large data sets. This method uses an adaptive scheme that renders the volume in a region-of-interest at a high resolution and the volume away from this region at progressively lower resolutions

A Review of Vessel Extraction Techniques and Algorithms

by Cemil Kirbas, Francis K. H. Quek - ACM Computing Surveys , 2000
"... Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by means of a classification of the existing r ..."
Abstract - Cited by 185 (0 self) - Add to MetaCart
research. While we have mainly targeted the extraction of blood vessels, neurosvascular structure in particular, we have also reviewed some of the segmentation methods for the tubular objects that show similar characteristics to vessels. We have divided vessel segmentation algorithms and techniques

Cell Segmentation with Adaptive Region Growing

by Dwi Anoraganingrum, Sabine Kröner, Björn Gottfried - ICIAP Venedig, Italy , 1999
"... The cell segmentation presented in this paper is part of current research work on an automated cell tracking project. Its aim is the tracking of the movement of representative cells in a 3D collagen gel in order to determine the activity of the cell after the injection of certain medical substances. ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
. A major requirement for this project is an efficient and robust method for the segmentation of cell images. Here we present an automated method based on region growing with a local adaptive threshold. For preprocessing we use an optimized rational filter for edge preserving noise smoothing

Gradient Based Seeded Region Grow method for CT Angiographic Image Segmentation

by Harikrishna Rai G. N
"... Abstract – Segmentation of medical images using seeded region growing technique is increasingly becoming a popular method because of its ability to involve high-level knowledge of anatomical structures in seed selection process. Region based segmentation of medical images are widely used in varied c ..."
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Abstract – Segmentation of medical images using seeded region growing technique is increasingly becoming a popular method because of its ability to involve high-level knowledge of anatomical structures in seed selection process. Region based segmentation of medical images are widely used in varied
Results 1 - 10 of 1,211