Olivier Barge

A Graph-based approach for Kite recognition

We propose a complete graph-based process for Kite recognition.We propose a geometric hierarchical graph matching solution to the problem of geometric graph matching.We also propose a benchmark of Kite graphs from real images.We experimentally evaluate our approach over both real and synthetic data sets. Display Omitted Kites are huge archaeological structures of stone visible from satellite images. Because of their important number and their wide geographical distribution, automatic recognition of these structures on images is an important step towards understanding these enigmatic remnants. This paper presents a complete identification tool relying on a graph representation of the Kites. As Kites are naturally represented by graphs, graph matching methods are thus the main building blocks in the Kite identification process. However, Kite graphs are disconnected geometric graphs for which traditional graph matching methods are useless. To address this issue, we propose a graph similarity measure adapted for Kite graphs. The proposed approach combines graph invariants with a geometric graph edit distance computation leading to an efficient Kite identification process. We analyze the time complexity of the proposed algorithms and conduct extensive experiments both on real and synthetic Kite graph data sets to attest the effectiveness of the approach. We also perform a set of experimentations on other data sets in order to show that the proposed approach is extensible and quite general.

Kite Recognition by Means of Graph Matching

Kites are remnants of long stone walls that outline the shape of a child’s kite. But the kites are huge, their big size makes them often clearly visible on high-resolution satellite images. Identified at first in the Near East, their area of distribution is getting larger and larger. This wide distribution gives new dimensions in the interpretation of these structures. Consequently, a large scale recognition of kites will help archeologists to understand the functionality of these enigmatic constructions. In this paper, we investigate how the satellite imagery can be exploited in this purpose using a graph representation of the kites. We propose a similarity measure and a kite identification process that can highlights the preservation state of the kites. We also construct from real images a benchmark of kite graphs that can be used by other researchers.