Delaunay triangulation-based features for camera-based document image retrieval system

被引：4

作者：

Dang, Q. B. ^{[1
]}

Rusinol, M. ^{[2
]}

Coustaty, M. ^{[1
]}

Luqman, M. M. ^{[1
]}

Tran, C. D. ^{[3
]}

Ogier, J-M. ^{[1
]}

机构：

[1] Univ La Rochelle, L3i Lab, La Rochelle, France

[2] Univ Autonoma Barcelona, CVC, E-08193 Barcelona, Spain

[3] Can Tho Univ, Coll Informat & Commun Technol, Can Tho, Vietnam

来源：

PROCEEDINGS OF 12TH IAPR WORKSHOP ON DOCUMENT ANALYSIS SYSTEMS, (DAS 2016) | 2016年

关键词：

Camera-based Document Image Retrieval; Delaunay Triangulation; feature descriptors; indexing; EFFICIENT;

D O I：

10.1109/DAS.2016.66

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a new feature vector, named DElaunay TRIangulation-based Features (DETRIF), for real-time camera-based document image retrieval. DETRIF is computed based on the geometrical constraints from each pair of adjacency triangles in delaunay triangulation which is constructed from centroids of connected components. Besides, we employ a hashing-based indexing system in order to evaluate the performance of DETRIF and to compare it with other systems such as LLAH and SRIF. The experimentation is carried out on two datasets comprising of 400 heterogeneous-content complex linguistic map images (huge size, 9800 X 11768 pixels resolution) and 700 textual document images.

引用

页码：1 / 6

页数：6

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