A unified framework for document restoration using inpainting and shape-from-shading

Zhang, Li; Yip, Andy M.; Brown, Michael S.; Tan, Chew Lim

doi:10.1016/j.patcog.2009.03.025

Cited by 65 publications

(48 citation statements)

References 56 publications

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“…This method is based on the assumptions that the document is either flat or smoothly curved and the camera is a standard pinhole camera. Finally, Tan et al [8] and L. Zhang et al [9] use a shape-from-shading formulation to reconstruct the 3-D shape of the document's surface. These techniques require knowledge of lighting, which in most of the cases, is unknown.…”

Section: A Rectification Techniques Based On 3-d Document Shape Recomentioning

confidence: 99%

“…Each word should be specified only from one baseline . Since the smaller absolute baseline slope and deviation is usually the most representative, the baseline of word is defined as if and otherwise (9) Examples of baseline estimation are given in Fig. 8.…”

Section: Coarse-to-fine Rectificationmentioning

confidence: 99%

“…Text distortions not only reduce document readability but also affect the performance of subsequent processing such as document layout analysis and optical character recognition (OCR). Over the last decade, many different techniques have been proposed for document image rectification [1] that can be classified into two main categories based on 1) 3-D document shape reconstruction [2]- [9] and 2) 2-D document image processing [10]- [24]. Techniques of the former category obtain the 3-D information of the document image using special setup or reconstruct the 3-D model from information existing in document images.…”

mentioning

confidence: 99%

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Goal-Oriented Rectification of Camera-Based Document Images

Stamatopoulos

Gatos

Pratikakis

et al. 2011

IEEE Trans. on Image Process.

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Abstract-Document digitization with either flatbed scanners or camera-based systems results in document images which often suffer from warping and perspective distortions that deteriorate the performance of current OCR approaches. In this paper, we present a goal-oriented rectification methodology to compensate for undesirable document image distortions aiming to improve the OCR result. Our approach relies upon a coarse-to-fine strategy. First, a coarse rectification is accomplished with the aid of a computationally low cost transformation which addresses the projection of a curved surface to a 2-D rectangular area. The projection of the curved surface on the plane is guided only by the textual content's appearance in the document image while incorporating a transformation which does not depend on specific model primitives or camera setup parameters. Second, pose normalization is applied on the word level aiming to restore all the local distortions of the document image. Experimental results on various document images with a variety of distortions demonstrate the robustness and effectiveness of the proposed rectification methodology using a consistent evaluation methodology that encounters OCR accuracy and a newly introduced measure using a semi-automatic procedure.Index Terms-Document image analysis, document image processing, document image rectification, image dewarping.

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Section: A Rectification Techniques Based On 3-d Document Shape Recomentioning

confidence: 99%

Section: Coarse-to-fine Rectificationmentioning

confidence: 99%

mentioning

confidence: 99%

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Goal-Oriented Rectification of Camera-Based Document Images

Stamatopoulos

Gatos

Pratikakis

et al. 2011

IEEE Trans. on Image Process.

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“…The majority of SFS methods proposed in literature [19,26,12] are based on the assumption that the light source is at infinity or at the optical centre of the camera. However, this assumption is not realistic for endoscopic applications.…”

Section: Sfs Depth Recovery From Video Imagementioning

confidence: 99%

Robust camera localisation with depth reconstruction for bronchoscopic navigation

2015

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Purpose Bronchoscopy is a standard technique for airway examination, providing a minimally invasive approach for both diagnosis and treatment of pulmonary diseases. To target lesions identified pre-operatively, it is necessary to register the location of the bronchoscope to the CT bronchial model during the examination. Existing vision-based techniques rely on the registration between virtually rendered endobronchial images and videos based on image intensity or surface geometry. However, intensity-based approaches are sensitive to illumination artefacts while gradient-based approaches are vulnerable to surface texture.Methods In this paper, depth information is employed in a novel way to achieve continuous and robust camera localisation. Surface shading has been used to recover depth from endobronchial images. The pose of the bronchoscopic camera is estimated by maximising the similarity between the depth recovered from a video image and that captured from a virtual camera projection of the CT model. The normalised cross-correlation and mutual information have both been used and compared for the similarity measure.Results The proposed depth-based tracking approach has been validated on both phantom and in vivo data. It outperforms the existing vision-based registration methods resulting in smaller pose estimation error of the bronchoscopic camera. It is shown that the proposed approach is more robust to illumination artefacts and surface texture and less sensitive to camera pose initialisation.

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“…Bhardwaj et al [8] presented a new technique for photo defect detection, by sensing the light after it passes through the photo and then thresholding the digitized image to identify defect objects. Zhang et al [9] proposed a framework, based on an inpainting algorithm, and a shape-from-shading technique, to remove unwanted distortions in digitized image from printed documents. Some state of the art algorithms for the detection and the restoration of specific defects in digitized degraded photos will be discussed in Section 2 .…”

Section: Introductionmentioning

confidence: 99%