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...

In this paper, we propose a new reflectance separation model to separate the diffuse and specular reflection components. The model is based on a two-dimensional space called Ch-CV space, which is spanned by maximum chromaticity and the coefficient of variation (CV) of RGB color. The space exhibits a more direct correspondence to diffuse and specular reflection components than the RGB color spac...

In this work, a new approach to region growing problem is presented. The region growing procedure is modified in order to apply a fuzzy knowledge based system to evaluate the distance between a pixel and the region. This fuzzy colour distance is based on a set of rules that evaluate the three distance components (R, G, B) jointly. The results presented show a improvement with the traditional cr...

Decomposing sensory measurements into coherent parts is a fundamental prerequisite for scene understanding that is required for solving complex tasks, e.g., in the field of mobile manipulation. In this article, we describe methods for efficient segmentation of range images and organized point clouds. In order to achieve real-time performance in complex environments, we focus our approach on sim...

In this paper we describe a region-oriented segmentation algorithm suited for the detection and extraction of large blood vessels in angiographic images. The algorithm is based on the mathematical morphology top-hat operator followed by a binary region growing process. The combination of these two steps generates an image containing only the largest vessels regions, allowing a fully automatic s...

This paper is concerned with the robust identiication of patches from simple geometric surfaces such as planes, spheres, and cylinders. This is done from 3D data acquired using a range scanner, along with principal quadric estimates at each point. Properties of the Gaussian and mean curvature (e.g., their sign) at points on surfaces of the target class are used to reject all points that could n...

In this paper, WC show how to extract reliable informations about the shape of 3D objects, obtained from volume medical images. We present an optimal region-growing algorithm, that makes use of the differential characteristics of the object surface, and achieves a stable segmentation into a set of patches of quadratic surfaces. We show how this segmentation can be used to recognize and locate a...

We present Easy Mesh Cutting, an intuitive and easy-to-use mesh cutout tool. Users can cut meaningful components from meshes by simply drawing freehand sketches on the mesh. Our system provides instant visual feedback to obtain the cutting results based on an improved region growing algorithm using a feature sensitive metric. The cutting boundary can be automatically optimized or easily edited ...