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 ...

A method for the automatic detection of buildings and their roof planes from LIDAR data and multispectral images is presented. For building detection, a classification technique is applied in a hierarchic way to overcome the problems encountered in areas of heterogeneous appearance of buildings. The detection of roof planes is based on a region growing algorithm applied to the LIDAR data, the s...

As the applications of the OCR are widely expanding recently, computers have to extract character patterns from various types of images such as scanned document images, scene images and video frames. Many methods for character pattern extraction have been proposed so far. They were designed and tuned for a special type of image and for a certain input device. However, we have many images which ...

A novel approach for segmentation of grayscale images, which are color scene originally, is proposed. Many algorithms have been elaborated for a grayscale image segmentation. All those approaches have been discussed in a luminance space, because it has been considered that grayscale images do not have any color information. However, a luminance value has color information as a set of correspond...

We propose a method for automatically correcting the spherical topology of any segmentation under any digital connectivity. A multiple region growing process, concurrently acting on the foreground and the background, divides the segmentation into connected components and successive minimum cost decisions guarantee convergence to correct spherical topology. In contrast to existing procedures tha...

Extracting textured objects from natural scenes is a challenging task in computer vision. The main difficulties arise from the intrinsic randomness of natural textures and the high-semblance between the objects and the background. In this paper, we approach the extraction problem with a seeded region-growing framework that purely exploits the statistical properties of intensity inhomogeneity. T...

High performance coding of image sequences requires efficient motion estimation and compensation. Block matching techniques are the usual choice. However they produce irregular motion fields and require subsequent regularization. This paper reports on a motion estimation technique that merges block matching with polynomial approximation and region growing to achieve such a regularization of the...