نتایج جستجو برای: region growing process

تعداد نتایج: 1951417  

Journal: :Image Vision Comput. 2014
Pierre Buyssens Isabelle Gardin Su Ruan Abderrahim Elmoataz

We describe an Eikonal-based algorithm for computing dense oversegmentation of an image, often called superpixels. This oversegmentation respect local image boundaries while limiting undersegmentation. The proposed algorithm relies on a region growing scheme, where the potential map used is not xed and evolves during the di usion. Re nement steps are also proposed to enhance at low cost the rst...

2006
Tomohiro Mizoguchi Hiroaki Date Satoshi Kanai Takeshi Kishinami

For effective application of laser or X-ray CT scanned mesh models in design, analysis, and inspection etc, it is preferable that they are segmented into desirable regions as a pre-processing. Engineering parts are commonly covered with analytic surfaces, such as planes, cylinders, spheres, cones, and tori. Therefore, the portions of the part’s boundary where each can be represented by a type o...

2004
Ali Benkhalil Valentina V. Zharkova Stanley S. Ipson Sergei I. Zharkov

In this paper techniques are described for the automated detection of solar Active Regions (ARs). AR detection is achieved using intensity thresholds and a region growing procedure. These procedures have been tested on full-disk solar images from the Meudon observatory for the months of April and July 2002 and compared with their manually generated synoptic maps. Comparisons were also made with...

Journal: :Signal Processing 1997
Jean-Philippe Thiran Vincent Warscotte Benoit M. Macq

Journal: :Pattern Recognition Letters 1993
J. P. Pascual Starink Ian T. Young

Starink, J.P.P. and I.T. Young, Localization of circular objects, Pattern Recognition Letters 14 ( 1993 ) 895-905. Localization of circular objects is easy when all objects are isolated, but becomes more complicated when two or more objects are touching or overlapping. In this paper we discuss a method to accurately localize the centroids and obtain estimates on the sizes. The method consists o...

2002
Lisa Kinnard Shih-Chung Ben Lo Paul C. Wang Matthew T. Freedman Mohamed F. Chouikha

This study attempted to accurately segment tumors in mammograms. Although this task is considered to be a preprocessing step in a computer analysis program, it plays an important role for further analysis of breast lesions. The region of interest (ROI) was segmented using the pixel aggregation and region growing techniques combined with maximum likelihood analysis. A fast segmentation algorithm...

Journal: :Pattern Recognition Letters 2001
Jing-Hao Xue Su Ruan Bruno Moretti Marinette Revenu Daniel Bloyet

8 In this paper, we propose a new knowledge-based method illustrated in the context of segmentation, which labels 9 internal brain structures viewed by magnetic resonance imaging (MRI). In order to improve the accuracy of the la10 beling, we introduce a fuzzy model of regions of interest (ROI) by analogy with the electrostatic potential distribution, 11 to represent more appropriately the knowl...

Journal: :CoRR 2014
Mohammed M. Abdelsamea

In this paper, an automatic seeded region growing algorithm is proposed for cellular image segmentation. First, the regions of interest (ROIs) extracted from the preprocessed image. Second, the initial seeds are automatically selected based on ROIs extracted from the image. Third, the most reprehensive seeds are selected using a machine learning algorithm. Finally, the cellular image is segment...

Journal: :Pattern Recognition 2014
Hsin-Ho Yeh Keng-Hao Liu Chu-Song Chen

This paper presents a new hybrid approach for detecting salient objects in an image. It consists of two processes: local saliency estimation and global-homogeneity refinement. We model the salient object detection problem as a region growing and competition process by propagating the influence of foreground and background seed-patches. First, the initial local saliency of each image patch is me...

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