Restoring Warped Document Image Based on Text Line Correction

[[abstract]]Document images captured by camera often suffer from warping and distortions because of the bounded volumes and complex environment light source. These effects not only reduce the document readability but also the OCR recognition performance. In this paper, we propose a method to combine non-linear and linear compensation for correcting distortions of document images. First, due to the broken text result of Otsu binarization, an image preprocessing is used to remove the effect of background light. Second, the dewarping method using the cubic polynomial fitting equation is proposed to find out the optimal approximate text line for vertical direction rectification. Finally, we use linear compensation for horizontal direction rectification. Experimental results demonstrate the robustness of the proposed methodology and improve the accuracy rate of OCR recognition.[[conferencetype]]國際[[conferencedate]]20130618~20130620[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Jeju Island, Republic of Kore

Innovative Techniques for Digitizing and Restoring Deteriorated Historical Documents

Recent large-scale document digitization initiatives have created new modes of access to modern library collections with the development of new hardware and software technologies. Most commonly, these digitization projects focus on accurately scanning bound texts, some reaching an efficiency of more than one million volumes per year. While vast digital collections are changing the way users access texts, current scanning paradigms can not handle many non-standard materials. Documentation forms such as manuscripts, scrolls, codices, deteriorated film, epigraphy, and rock art all hold a wealth of human knowledge in physical forms not accessible by standard book scanning technologies. This great omission motivates the development of new technology, presented by this thesis, that is not-only effective with deteriorated bound works, damaged manuscripts, and disintegrating photonegatives but also easily utilized by non-technical staff. First, a novel point light source calibration technique is presented that can be performed by library staff. Then, a photometric correction technique which uses known illumination and surface properties to remove shading distortions in deteriorated document images can be automatically applied. To complete the restoration process, a geometric correction is applied. Also unique to this work is the development of an image-based uncalibrated document scanner that utilizes the transmissivity of document substrates. This scanner extracts intrinsic document color information from one or both sides of a document. Simultaneously, the document shape is estimated to obtain distortion information. Lastly, this thesis provides a restoration framework for damaged photographic negatives that corrects photometric and geometric distortions. Current restoration techniques for the discussed form of negatives require physical manipulation to the photograph. The novel acquisition and restoration system presented here provides the first known solution to digitize and restore deteriorated photographic negatives without damaging the original negative in any way. This thesis work develops new methods of document scanning and restoration suitable for wide-scale deployment. By creating easy to access technologies, library staff can implement their own scanning initiatives and large-scale scanning projects can expand their current document-sets

A Book Reader Design for Persons with Visual Impairment and Blindness

The objective of this dissertation is to provide a new design approach to a fully automated book reader for individuals with visual impairment and blindness that is portable and cost effective. This approach relies on the geometry of the design setup and provides the mathematical foundation for integrating, in a unique way, a 3-D space surface map from a low-resolution time of flight (ToF) device with a high-resolution image as means to enhance the reading accuracy of warped images due to the page curvature of bound books and other magazines. The merits of this low cost, but effective automated book reader design include: (1) a seamless registration process of the two imaging modalities so that the low resolution (160 x 120 pixels) height map, acquired by an Argos3D-P100 camera, accurately covers the entire book spread as captured by the high resolution image (3072 x 2304 pixels) of a Canon G6 Camera; (2) a mathematical framework for overcoming the difficulties associated with the curvature of open bound books, a process referred to as the dewarping of the book spread images, and (3) image correction performance comparison between uniform and full height map to determine which map provides the highest Optical Character Recognition (OCR) reading accuracy possible. The design concept could also be applied to address the challenging process of book digitization. This method is dependent on the geometry of the book reader setup for acquiring a 3-D map that yields high reading accuracy once appropriately fused with the high-resolution image. The experiments were performed on a dataset consisting of 200 pages with their corresponding computed and co-registered height maps, which are made available to the research community (cate-book3dmaps.fiu.edu). Improvements to the characters reading accuracy, due to the correction steps, were quantified and measured by introducing the corrected images to an OCR engine and tabulating the number of miss-recognized characters. Furthermore, the resilience of the book reader was tested by introducing a rotational misalignment to the book spreads and comparing the OCR accuracy to those obtained with the standard alignment. The standard alignment yielded an average reading accuracy of 95.55% with the uniform height map (i.e., the height values of the central row of the 3-D map are replicated to approximate all other rows), and 96.11% with the full height maps (i.e., each row has its own height values as obtained from the 3D camera). When the rotational misalignments were taken into account, the results obtained produced average accuracies of 90.63% and 94.75% for the same respective height maps, proving added resilience of the full height map method to potential misalignments

A unified framework for document image restoration

Ph.DDOCTOR OF PHILOSOPH

DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction

In this work, we propose a new framework, called Document Image Transformer (DocTr), to address the issue of geometry and illumination distortion of the document images. Specifically, DocTr consists of a geometric unwarping transformer and an illumination correction transformer. By setting a set of learned query embedding, the geometric unwarping transformer captures the global context of the document image by self-attention mechanism and decodes the pixel-wise displacement solution to correct the geometric distortion. After geometric unwarping, our illumination correction transformer further removes the shading artifacts to improve the visual quality and OCR accuracy. Extensive evaluations are conducted on several datasets, and superior results are reported against the state-of-the-art methods. Remarkably, our DocTr achieves 20.02% Character Error Rate (CER), a 15% absolute improvement over the state-of-the-art methods. Moreover, it also shows high efficiency on running time and parameter count. The results will be available at https://github.com/fh2019ustc/DocTr for further comparison.Comment: This paper has been accepted by ACM Multimedia 202

Captured open book image de-warping and shading correction using 3D depth information

Various three dimensional (3D) measuring or capturing devices are introduced to the society recently, and there are abundant possibilities that we can take advantage of this new technology. In this research, we worked on one useful application: to correct the distortion due to the curved shape of the pages of an open book in captured images using of depth information. This work is relevant to camera-based capture devices that can use a projector to cast structured light patterns to provide depth information. In order to improve the visual quality of captured documents, we established our algorithm from two perspectives. First, we deal with the shading situation in the captured image as a result of the non-uniform lighting condition. The shading correction is based on the shading information of the margin of the document, or based on the estimated relative position of each piece of the scanned open book to the active illumination. The open book will look like it is captured under a uniform lighting source in the corrected images. Next, we handle the geometric distortion. The 3D shape reconstruction methods and geometric rectification are used to flatten the curvature of an open book. The models we used exploit specific prior assumptions about the nature of the printed material that is captured. The warped text line can be straightened after this rectification. The overall readability improvement in captured open book images obtained by using our method can be observed in the experimental results