Abstract—A hybrid multidimensional image segmentation algorithm is proposed, which combines edge and region-based techniques through the morphological algorithm of watersheds. An edge-preserving statistical noise reduction approach is used as a preprocessing stage in order to compute an accurate estimate of the image gradient. Then, an initial partitioning of the image into primitive regions is produced by applying the watershed transform on the image gradient magnitude. This initial segmentation is the input to a computationally efficient hierarchical (bottomup) region merging process that produces the final segmentation. The latter process uses the region adjacency graph (RAG) representation of the image regions. At each step, the most similar pair of regions is determined (minimum cost RAG edge), the regions are merged and the RAG is updated. Traditionally, the above is implemented by storing all RAG edges in a priority queue. We propose a significantly faster algorithm, which additionally maintains the so-called nearest neighbor graph, due to which the priority queue size and processing time are drastically reduced. The final segmentation provides, due to the RAG, one-pixel wide, closed, and accurately localized contours/surfaces. Experimental results obtained with two-dimensional/three-dimensional (2-D/3-D) magnetic resonance images are presented. Index Terms — Image segmentation, nearest neighbor region merging, noise reduction, watershed transform. I.

This paper discusses region-based representations of image and video that are useful for multimedia services such as those supported by the MPEG-4 and MPEG-7 standards. Classical tools related to the generation of the region-based representations are discussed. After a description of the main processing steps and the corresponding choices in terms of feature spaces, decision spaces, and decision algorithms, the state of the art in segmentation is reviewed. Mainly tools useful in the context of the MPEG-4 and MPEG-7 standard are discussed. The review is structured around the strategies used by the algorithms (transition-based or homogeneity-based) and the decision spaces (spatial, spatio-temporal and temporal). The second part of the paper proposes a partition tree representation of images and introduces a processing strategy that involves a similarity estimation step followed by a partition creation step. This strategy tries to find a compromise between what can be done in...

This paper presents a region-based coding algorithm for video sequences. The coding approach involves a time-recursive segmentation relying on the pixels homogeneity, a region-based motion estimation, and motion compensated contour and texture coding. This algorithm is mainly devoted to very low bit rate video coding applications. One of the important features of the approach is that no assumption is made about the sequence content. Moreover, the algorithm structure leads to a scalable coding process giving various levels of quality and bit rates. The coding as well as the segmentation are controlled to regulate the bit stream. Finally, the interest of morphological tools in the context of region-based coding is extensively reviewed. Keywords--- Video coding, mathematical morphology, segmentation, motion estimation and compensation, contour coding, texture coding. I. Introduction I N the framework of very low bit rate video coding, there is an increasing interest in second generation...

This paper deals with the use of some morphological tools for image and video coding. Mathematical morphology can be considered as a shape-oriented approach to signal processing and some of its features make it very useful for compression. Rather than describing a coding algorithm, the purpose of this paper is to describe some morphological tools that have recently proved to be attractive for compression. Four sets of morphological transformations are presented: connected operators, the region growing version of the watershed, the geodesic skeleton and a morphological interpolation technique. Their implementation will be discussed and we will show how they can be used for image and video segmentation, for contour coding and for texture coding. I. Introduction I MAGE and video compression techniques generally rely on the results of the information theory. In this framework, compression is achieved by a decorrelation of the signal followed by quantization and entropy coding of the infor...

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This paper presents a generic video coding algorithm allowing the content-based manipulation of objects. This manipulation is possible thanks to the definition of a spatio-temporal segmentation of the sequences. The coding strategy relies on a joint optimization in the Rate-Distortion sense of the partition definition and of the coding techniques to be used within each region. This optimization creates the link between the analysis and synthesis parts of the coder. The analysis defines the time evolution of the partition, as well as the elimination or the appearance of regions that are homogeneous either spatially or in motion. The coding of the texture as well as of the partition relies on region-based motion compensation techniques. The algorithm offers a good compromise between the ability to track and manipulate objects and the coding efficiency. Keywords--- Video coding, Region-based coding, Spatiotemporal segmentation, Rate-distortion optimization, Affine motion estimation and c...

We introduce a novel region-based video compression framework based on morphology to efficiently capture motion correspondences between consecutive frames in an image sequence. Our coder is built on the observation that the motion field associated with typical image sequences can be segmented into component motion subfield "clusters" associated with distinct objects or regions in the scene, and further that these clusters can be efficiently captured using morphological operators in a "backward" framework that avoids the need to send region shape information. Region segmentation is performed directly on the motion field by introducing a small "core" for each cluster that captures the essential features of the cluster and reliably represents its motion behavior. Cluster matching is used in lieu of the conventional block matching methods of standard video coders to define a cluster motion representation paradigm. Furthermore, a region-based pel-recursive approach is applied to f...

We introduce a novel region-based video compression framework based on morphology to efficiently capture motion correspondences between consecutive frames in an image sequence. Our coder is built on the observation that the motion field associated with typical image sequences can be segmented into component motion subfield "clusters" associated with distinct objects or regions in the scene, and further that these clusters can be efficiently captured using morphological operators in a "backward" framework that avoids the need to send region shape information. Region segmentation is performed directly on the motion field by introducing a small "core" for each cluster that captures the essential features of the cluster and reliably represents its motion behaviour. Cluster matching is used in lieu of the conventional block matching methods of standard video codecs to define a cluster motion representation paradigm. Furthermore, a region-based pel-recursive approach is applied to find the r...

this paper, is based on pure motion information keeping the framework of model compliance and model failure regions of [12]. However, the object hierarchy is reverted so as to proceed from smaller objects to larger ones, thus allowing a more exible segmentation which is closer to the optimum partition and which is applicable to a more general class of image sequences. The bottom-up scheme is superior to the top-down approachin that a) object detail can be controlled at any resolution level, b) the chance of missing small but semantically relevant objects, suchaseyes and mouth in videophony is minimized, c) the scheme is independent of the scene content. On the contrary the top-down scheme can miss semantically important details and it is too much oriented towards head-and-shoulder scenes. The proposed scheme is based on region growing and region merges with re-estimation of the motion parameters after a joint operation

A novel motion-based object-oriented codec for video transmission at very low bit-rates is proposed. The object motion is modeled by quadratic transform with coe$cients estimated via a nonlinear quasi-Newton method. The segmentation problem is put forward as a constrained optimization problem which interacts with the motion estimation process in the course of region growing. A context-based shape coding method which takes into account the image synthesis error as well as the geometric distortion, is also proposed. Quantitative and subjective performance results of the codec on various test sequences illustrate the superior performance of the method. � 2000 Elsevier Science B.V. All rights reserved. Keywords: Object-oriented video coding; Motion segmentation; Region growing; Quadratic transform; Shape polygonization