Quoc Bao Dang, Marçal Rusiñol, Mickaël Coustaty, M. Luqman, De Cao Tran, J. Ogier
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引用次数: 4
Abstract
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.
在本文中，我们提出了一种新的特征向量，称为DElaunay TRIangulation-based Features (DETRIF)，用于基于相机的实时文档图像检索。DETRIF是基于delaunay三角剖分中每对邻接三角形的几何约束来计算的，delaunay三角剖分是由连通分量的质心构成的。此外，我们采用了一个基于哈希的索引系统来评估DETRIF的性能，并将其与LLAH和SRIF等其他系统进行比较。实验在两个数据集上进行，其中包括400张异构内容复杂语言地图图像(超大尺寸，分辨率为9800 X 11768像素)和700张文本文档图像。
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