Fast Restoration of Warped Document Image based on Text Rectangle Area Segmentation

Abstract

<p class="Default">The warp problems usually make the documents being hardly recognized. Specifically, when we copy a page of a thick book or bound document by digital photocopier, the resulted image is usually warped because of the thickness of the document. We focus on this problem and propose a fast method to restore the warped document image in this paper. The text rectangle area of the document is one of the features of a document. The morphological operation is utilized for text rectangle area segmentation. The DLT method is used to compute the mapping relations between the warped document and the non-warped document. In experimental results, the proposed method works on high resolution image very quickly. The warping text and the figures in documents have been restored by the proposed method successfully. This method is efficiency and fast for implementing on the module of digital photocopier.</p

Restoring camera-captured distorted document images

“…The main idea of the model is to build up the correspondence between a rectangle region on a flat surface and its curved region on the distorted book image, and the dewarping task is to flatten the curved region to its original rectangle shape. Recently, Hsia et al [16] proposed a method based on text rectangle area segmentation which is a fast method. Stamatopoulos et al [17] address the projection of a curved surface into a 2D rectangular area.…”

“…It is the best in arbitrary shape cases; however, it seems to be too complicated and no data about the algorithm speed are reported. Hsia's work [16] uses the DLT method to compute the mapping relations between the warped document and the non-warped document. These methods all divide the whole image into small parts and restore each part with a projective transformation.…”

“…Present model-free dewarping methods mainly focus on shape estimation stage, and various curled text line segmentation methods have been put forward. Parts of approaches directly estimate distorted shape of text block or paragraph by either rectangle area or other geometric model [15,16], but information inside text lines and characters is thus ignored which leads to estimation error when text block borders are not so clear. Some proposed methods combining curled line segmentation and baseline estimation, for example, by coupled snakes [14].…”

Minimum Error Thresholding Segmentation Algorithm Based on 3D Grayscale Histogram

“…Image segmentation is an essential procedure to analyze the image structure as other processing steps heavily depend on its results, and a wide variety of segmentation techniques have been reported in the last two decades. Some of its applications relate to many fields, such as medical imaging [1,2], document analysis [3,4], object recognition [5], and SAR segmentation and quality inspection of materials [6].…”