Abstract

The importance of building an objective and accurate benchmarking platform for document layout analysis (DLA) algorithms has been realized by more and more researchers. In this paper, an experimental benchmarking framework for DLA algorithms is proposed. Firstly, a ground-truth database is built where test images and expected layout analysis results for corresponding image are stored. Secondly, the analysis result of a certain test image given by a DLA algorithm is evaluated based on the expected results in the ground-truth database, and a performance metric is given. It is also important to note that the reasonable layout analysis result for a given image might not be unique. Therefore, we implemented a flexible learning mechanism into our framework to get a more accurate performance metric. In the end, we apply our framework to the benchmarking of a document layout analysis algorithm and the experimental results are given.

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