This paper focuses on flood-region detection using monitoring images. However, adverse weather affects the outcome of image segmentation methods. In this paper, we present an experimental comparison of an outdoor visual sensing system using region-growing methods with two different growing rules-namely, GrowCut and RegGro. For each growing rule, several tests on adverse weather and lens-stained...

Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds individual points or connected components that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm i...

To cope with the difficulty of 3D MRI brain scans segmentation, specification and instantiation of a priori models should be constrained by local images characteristics. We introduce situated cooperative agents for the extraction of domain and control knowledge from image grey levels. Their dedicated behaviours, i.e segmentation of one type of tissue, are dynamically adapted function of their p...

We develop an algorithm to segment a 3D surface mesh intovisually meaningful regions based on analyzing the local geometry ofvertices. We begin with a novel characterization of mesh vertices as convex,concave or hyperbolic depending upon their discrete local geometry.Hyperbolic and concave vertices are considered potential feature regionboundaries. We propose a new region growing technique star...

This paper presents the region based segmentation method for ultrasound images using local statistics. In this segmentation approach the homogeneous regions depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are to be extracted. This method uses a look up table comprising of the local statistics of every pixel, which are con...

This work presents a region-growing image segmentation approach based on superpixel decomposition. From an initial contour-constrained over-segmentation of the input image, the image segmentation is achieved by iteratively merging similar superpixels into regions. This approach raises two key issues: (1) how to compute the similarity between superpixels in order to perform accurate merging and ...

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 paper presents a parallel version for the Propagation Algorithm which belongs to the region growing family of algorithms. The main goal of our implementation is to decrease de Propagation Algorithm execution time in order to allow its use on image interpolation applications. Our solution is oriented to low cost high performance platforms such as clusters of workstations. Four different inp...

In this paper we present a region growing approach for color images using an online learning algorithm that aims for content-based image retrieval systems. Our learning algorithm follows a variation of Bayesian estimation procedure to characterize each region as it is grown. The resulting image growing procedure is simple to implement, robust to initial parameters and has a linear complexity. R...

The technique which is presented here is based on careful attention to image cleaning in order to achieve robust automatic filament detection and avoid confusion between filaments and image defects, due to particular shapes of filaments. The main part of the detection process is based on seed selection and region growing. The procedures developed have been tested on four months of full-disk ima...