A novel segmentation algorithm based on the region growing paradigm is presented. Unlike previous segmentation methods, this novel scheme requires neither hand-tuning of parameters nor knowledge about the scene. Instead, the parameter which controls the segmentation is dynamically derived from the data for each region, based on a local quality measure of the region's contour. The algorithm assi...

AbstractIn spite of their non-isotropic nature, local growths based on 4-connected or 8-connected neighborhoods are frequently used for binary image dilation, mostly because they are very easy to implement. Altough better dilation techniques exist, they usually require bigger masks, more complex routines, exotical grid definitions or globally processing the image. In this article we propose a n...

Of the many proposed image segmentation methods, region growing has been one of the most popular. Research on region growing, however, has focused primarily on the design of feature measures and on growing and merging criteria. Most of these methods have an inherent dependence on the order in which the points and regions are examined. This weakness implies that a desired segmented result is sen...

We present a model-driven approach to the segmentation of nasal cavity and paranasal sinus boundaries. Based on computed tomography data of a patients head, our approach aims to extract the border that separates the structures of interest from the rest of the head. This three-dimensional region information is useful in many clinical applications, e.g. diagnosis, surgical simulation, surgical pl...

In this paper a new approach to CT based investigation of pulmonary airways is introduced. Especially a new fully automated algorithm for airway tree segmentation is proposed. The algorithm is based on 3D seeded region growing. However in opposite to traditional approaches region growing is applied twice: firstly – for detecting main bronchi, secondly – for localizing low order parts of the air...

This article presents a novel 3D planar patch extraction method using a probabilistic region growing algorithm. Our method works by simultaneously initiating multiple planar patches from seed points, the latter determined by an intensity-based 2D segmentation algorithm in the stereopair images. The patches are grown incrementally and in parallel as 3D scene points are considered for membership,...

In this paper, a target tracking algorithm is proposed by combining the improved Mean Shift algorithm with the adaptive Kalman filter. For a selected moving object, frame difference and region growing methods are used to segment target and extract the dominant color. In the tracking process, the initial iterative position is obtained by adaptive Kalman filter in each frame. The tracking result ...

This report reviews selected image binarization and segmentation methods that have been proposed and which are suitable for the processing of volume images. The focus is on thresholding, region growing, and shape–based methods. Rather than trying to give a complete overview of the field, we review the original ideas and concepts of selected methods, because we believe this information to be imp...