Text extraction in complex color documents

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摘要

Text extraction in mixed-type documents is a pre-processing and necessary stage for many document applications. In mixed-type color documents, text, drawings and graphics appear with millions of different colors. In many cases, text regions are overlaid onto drawings or graphics. In this paper, a new method to automatically detect and extract text in mixed-type color documents is presented. The proposed method is based on a combination of an adaptive color reduction (ACR) technique and a page layout analysis (PLA) approach. The ACR technique is used to obtain the optimal number of colors and to convert the document into the principal of them. Then, using the principal colors, the document image is split into the separable color plains. Thus, binary images are obtained, each one corresponding to a principal color. The PLA technique is applied independently to each of the color plains and identifies the text regions. A merging procedure is applied in the final stage to merge the text regions derived from the color plains and to produce the final document. Several experimental and comparative results, exhibiting the performance of the proposed technique, are also presented.

论文关键词:Color segmentation,Color documents,Color quantization,Neural networks,Text extraction,Page layout analysis

论文评审过程:Received 5 July 2001, Available online 12 April 2002.

论文官网地址:https://doi.org/10.1016/S0031-3203(01)00167-4