. We introduce a very general method of achieving stable and fast color segmentation. This method works on different hierarchical data structures and combines local bottom-up region growing segmentation with top-down separation techniques. As our method supports exploitation of inherent parallelism, a real-time object detection has been designed and is in the implementation phase. 1 Introduction Image segmentation is an important step towards an object detection in image analysis. In the literature several major methods for segmentation are distinguished [4]. Common are edge-detection, region-growing and clustering techniques. Whilst clustering uses mainly statistical methods, syntactical methods are more popular for edge-detection and region-growing techniques. Regiongrowing methods are usually classified as local, global or splitting-and-merging techniques. Local techniques are simple and fast, but have the problem of chaining: two very dissimilar pixels may be connected by a chain..
