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...

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...

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...

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...

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...

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...

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...

. Automatic liver segmentation plays an important role in computer-aided diagnosis and treatment. Manual segmentation of organs is a difficult and tedious task and so prone to human errors. In this paper, we propose an adaptive 3D region growing with subject-specific conditions. For this aim we use the intensity distribution of most probable voxels in prior map along with location prior. We als...

Text in images and video frames carries important information for visual content understanding and retrieval. In this paper, by using multiscale wavelet features, we propose a novel coarse-to-fine algorithm that is able to locate text lines even under complex background. First, in the coarse detection, after the wavelet energy feature is calculated to locate all possible text pixels, a density-...