Abstract: The main idea of graph based image modeling is that the regions of the image, which contain similar properties, are denoted by graph vertices, and the relations between different regions are denoted by graph edges. The vertex and edge attributes usually describe the characteristics of that region and the relation between regions respectively. A simple approach to keep the structural and topological information of an image is to use digital image representation techniques; for instance, quad trees, etc. By modeling images as graphs, the task of image classification becomes one of classifying graphs. Quad trees have been used for representing images in the form of trees. In this paper we propose an algorithm that discovers the subgr...
PP.385-389International audienceAutomatic object recognition plays a central role in numerous applic...
From its early stages, the community of Pattern Recognition and Computer Vision has considered the i...
Graphs are a powerful and versatile data structure for pattern recognition. However, their flexibili...
This paper presents a new method for segmentation and recognition of image objects based on structur...
We present three new algorithms to model images with graph primitives. Our main goal is to propose a...
An image contains a lot of information, and that information can be used in high-level complex syste...
On the one hand, the solution of computer vision tasks is associated with the development of various...
This work presents a method for object recognition in digital images based on Graph Theory. We aim a...
International audienceMany image processing and image segmentation problems, in two or three dimensi...
This book will serve as a foundation for a variety of useful applications of graph theory to compute...
The generalization capability is usually recognized as the most desired feature of data-driven learn...
Graph-based data representations are an important research topic due to the suitability of this kind...
There are several methods for categorizing images, the most of which are statistical, geometric, mod...
In this paper, we show that simple edge characteristics in images, when judiciously combined, can re...
Many approaches to image classification tend to transform an image into an unstructured set of numer...
PP.385-389International audienceAutomatic object recognition plays a central role in numerous applic...
From its early stages, the community of Pattern Recognition and Computer Vision has considered the i...
Graphs are a powerful and versatile data structure for pattern recognition. However, their flexibili...
This paper presents a new method for segmentation and recognition of image objects based on structur...
We present three new algorithms to model images with graph primitives. Our main goal is to propose a...
An image contains a lot of information, and that information can be used in high-level complex syste...
On the one hand, the solution of computer vision tasks is associated with the development of various...
This work presents a method for object recognition in digital images based on Graph Theory. We aim a...
International audienceMany image processing and image segmentation problems, in two or three dimensi...
This book will serve as a foundation for a variety of useful applications of graph theory to compute...
The generalization capability is usually recognized as the most desired feature of data-driven learn...
Graph-based data representations are an important research topic due to the suitability of this kind...
There are several methods for categorizing images, the most of which are statistical, geometric, mod...
In this paper, we show that simple edge characteristics in images, when judiciously combined, can re...
Many approaches to image classification tend to transform an image into an unstructured set of numer...
PP.385-389International audienceAutomatic object recognition plays a central role in numerous applic...
From its early stages, the community of Pattern Recognition and Computer Vision has considered the i...
Graphs are a powerful and versatile data structure for pattern recognition. However, their flexibili...