Exploiting 2D Topology in Labeling Polyhedral Images

نویسنده

  • Van-Duc Nguyen
چکیده

Abftract: A polyhedral image is a segmentation of the image plane into connected regions, called faces, joined by vertices and edges. The segmentation is represented by a planar network of nodes (vertices, edges, faces) linked by adjacency links. The labeling constraints at a node are all local labelings of the node consistent with itself and all its adjacent neighbors. The local labelings are represented by junctions, junction-pairs, and junction-loops respectively for the vertices, edges, and face boundaries of the image. Constraint satisfaction and propagation is done uniformly over all nodes in the image, from each node to its adjacent neighbors. The result is local consistency or inconsistency at all the nodes in the planar network. We show that globally consistent labelings of the image exist, if and only if all the nodes in the network have locally consistent labelings. The planar network of nodes, with labels and local labelings attached to each node, represents all locally/globally consistent labelings of the polyhedral image. 1. A Labeling Example Figure 1 traces the parallel labeling of two blocks, one on top of the other. The parallel labeling starts with the input image and default labels (?) for all the nodes (i.e., vertices, edges, and faces) in the image. Then, it finds all local labeling constraints at all vertices, edges, and face boundaries of the image, described respectively by junctions, junction-pairs, and junction-loops, frames 1 to 3. Attached to each node is the number of local labelings. Constraint satisfaction and propagation (CSP) is done uniformly at all nodes in the image, from every node to its neighbors, through vertex-edge, edge-face, and face-vertex links. Note the decrease in the number of local labelings at each node, frames 4 to 6. The face surrounding the two blocks has 16 local labelings, corresponding to the blocks floating in air, or resting against some imaginary surface at some of its bounding edges. The two interpretations correspond to the face labeled as image background (B) or as polyhedral face (F). Note that the blocks sitting on top of a horizontal surface can be thought as the blocks floating in air, and infinitesimally touching the surface. The surrounding face is a touchable background, and so is labeled by 8, and has only 1 junction-loop. The detection of the background face surrounding the blocks further restricts the labeling of the blocks, Frames 7 and 8 show the final labels at the …

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Image sequence segmentation combining global labeling and local relabeling and its application to materials science images

Accurately segmenting a series of 2D serial-sectioned images for multiple, contiguous 3D structures has important applications in medical image processing, video sequence analysis, and materials science image segmentation. While 2D structure topology is largely consistent across consecutive serial sections, it may vary locally because a 3D structure of interest may not span the entire 2D sequen...

متن کامل

Graph Cut Approaches for Materials Segmentation Preserving Shape, Appearance, and Topology

Segmenting material images into underlying objects is an important but challenging problem given object complexity and image noise. Consistency of shape, appearance, and topology among the underlying objects are critical properties of materials images and can be considered as criteria to improve segmentation. For example, some materials may have objects with a specific shape or appearance in ea...

متن کامل

Using Membrane Computing for Obtaining Homology Groups of Binary 2D Digital Images

Membrane Computing is a new paradigm inspired from cellular communication. Until now, P systems have been used in research areas like modeling chemical process, several ecosystems, etc. In this paper, we apply P systems to Computational Topology within the context of the Digital Image. We work with a variant of P systems called tissuelike P systems to calculate in a general maximally parallel m...

متن کامل

3D Model-Based Semantic Categorization of Still Image 2D Objects

Automatic classification and interpretation of objects present in 2D images is a key issue for various computer vision applications. In particular, when considering image/video, indexing, and retrieval applications, automatically labeling in a semantically pertinent manner/huge multimedia databases still remains a challenge. This paper examines the issue of still image object categorization. Th...

متن کامل

3D Model-Based Semantic Categorization of Still Image 2D Objects

Automatic classification and interpretation of objects present in 2D images is a key issue for various computer vision applications. In particular, when considering image/video, indexing, and retrieval applications, automatically labeling in a semantically pertinent manner/huge multimedia databases still remains a challenge. This paper examines the issue of still image object categorization. Th...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1987