Retrospective Illumination Correction of Retinal Images

A method for correction of nonhomogenous illumination based on optimization of parameters of B-spline shading model with respect to Shannon's entropy is presented. The evaluation of Shannon's entropy is based on Parzen windowing method (Mangin, 2000) with the spline-based shading model. This allows us to express the derivatives of the entropy criterion analytically, which enables efficient use of gradient-based optimization algorithms. Seven different gradient- and nongradient-based optimization algorithms were initially tested on a set of 40 simulated retinal images, generated by a model of the respective image acquisition system. Among the tested optimizers, the gradient-based optimizer with varying step has shown to have the fastest convergence while providing the best precision. The final algorithm proved to be able of suppressing approximately 70% of the artificially introduced non-homogenous illumination. To assess the practical utility of the method, it was qualitatively tested on a set of 336 real retinal images; it proved the ability of eliminating the illumination inhomogeneity substantially in most of cases. The application field of this method is especially in preprocessing of retinal images, as preparation for reliable segmentation or registration

From Damage to Discovery Via Virtual Unwrapping: Reading the Scroll from En-Gedi

Computer imaging techniques are commonly used to preserve and share readable manuscripts, but capturing writing locked away in ancient, deteriorated documents poses an entirely different challenge. This software pipeline—referred to as “virtual unwrapping”—allows textual artifacts to be read completely and noninvasively. The systematic digital analysis of the extremely fragile En-Gedi scroll (the oldest Pentateuchal scroll in Hebrew outside of the Dead Sea Scrolls) reveals the writing hidden on its untouchable, disintegrating sheets. Our approach for recovering substantial ink-based text from a damaged object results in readable columns at such high quality that serious critical textual analysis can occur. Hence, this work creates a new pathway for subsequent textual discoveries buried within the confines of damaged materials

Robust virtual unrolling of historical parchment XMT images

We develop a framework to virtually unroll fragile historical parchment scrolls, which cannot be physically unfolded via a sequence of X-ray tomographic slices, thus providing easy access to those parchments whose contents have remained hidden for centuries. The first step is to produce a topologically correct segmentation, which is challenging as the parchment layers vary significantly in thickness, contain substantial interior textures and can often stick together in places. For this purpose, our method starts with linking the broken layers in a slice using the topological structure propagated from its previous processed slice. To ensure topological correctness, we identify fused regions by detecting junction sections, and then match them using global optimization efficiently solved by the blossom algorithm, taking into account the shape energy of curves separating fused layers. The fused layers are then separated using as-parallel-as-possible curves connecting junction section pairs. To flatten the segmented parchment, pixels in different frames need to be put into alignment. This is achieved via a dynamic programming-based global optimization, which minimizes the total matching distances and penalizes stretches. Eventually, the text of the parchment is revealed by ink projection. We demonstrate the effectiveness of our approach using challenging real-world data sets, including the water damaged fifteenth century Bressingham scroll

Interactive Exploration and Flattening of Deformed Historical Documents

We present an interactive application for browsing severely damaged documents and other cultural artefacts. Such documents often contain strong geometric distortions such as wrinkling, buckling, and shrinking and cannot be flattened physically due to the high risk of causing further damage. Previous methods for virtual restoration involve globally flattening a 3D reconstruction of the document to produce a static image. We show how this global approach can fail in cases of severe geometric distortion, and instead propose an interactive viewer which allows a user to browse a document while dynamically flattening only the local region under inspection. Our application also records the provenance of the reconstruction by displaying the reconstruction side by side with the original image data

A Survey of Geometric Analysis in Cultural Heritage

We present a review of recent techniques for performing geometric analysis in cultural heritage (CH) applications. The survey is aimed at researchers in the areas of computer graphics, computer vision and CH computing, as well as to scholars and practitioners in the CH field. The problems considered include shape perception enhancement, restoration and preservation support, monitoring over time, object interpretation and collection analysis. All of these problems typically rely on an understanding of the structure of the shapes in question at both a local and global level. In this survey, we discuss the different problem forms and review the main solution methods, aided by classification criteria based on the geometric scale at which the analysis is performed and the cardinality of the relationships among object parts exploited during the analysis. We finalize the report by discussing open problems and future perspectives

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

텍스트와 특징점 기반의 목적함수 최적화를 이용한 문서와 텍스트 평활화 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 8. 조남익.There are many techniques and applications that detect and recognize text information in the images, e.g., document retrieval using the camera-captured document image, book reader for visually impaired, and augmented reality based on text recognition. In these applications, the planar surfaces which contain the text are often distorted in the captured image due to the perspective view (e.g., road signs), curvature (e.g., unfolded books), and wrinkles (e.g., old documents). Specifically, recovering the original document texture by removing these distortions from the camera-captured document images is called the document rectification. In this dissertation, new text surface rectification algorithms are proposed, for improving text recognition accuracy and visual quality. The proposed methods are categorized into 3 types depending on the types of the input. The contributions of the proposed methods can be summarized as follows. In the first rectification algorithm, the dense text-lines in the documents are employed to rectify the images. Unlike the conventional approaches, the proposed method does not directly use the text-line. Instead, the proposed method use the discrete representation of text-lines and text-blocks which are the sets of connected components. Also, the geometric distortion caused by page curl and perspective view are modeled as generalized cylindrical surfaces and camera rotation respectively. With these distortion model and discrete representation of the features, a cost function whose minimization yields parameters of the distortion model is developed. In the cost function, the properties of the pages such as text-block alignment, line-spacing, and the straightness of text-lines are encoded. By describing the text features using the sets of discrete points, the cost function can be easily defined and well solved by Levenberg-Marquadt algorithm. Experiments show that the proposed method works well for the various layouts and curved surfaces, and compares favorably with the conventional methods on the standard dataset. The second algorithm is a unified framework to rectify and stitch multiple document images using visual feature points instead of text lines. This is similar to the method employed in general image stitching algorithm. However, the general image stitching algorithm usually assumes fixed center of camera, which is not taken for granted in capturing the document. To deal with the camera motion between images, a new parametric family of motion model is proposed in this dissertation. Besides, to remove the ambiguity in the reference plane, a new cost function is developed to impose the constraints on the reference plane. This enables the estimation of physically correct reference plane without prior knowledge. The estimated reference plane can also be used to rectify the stitching result. Furthermore, the proposed method can be applied to any other planar object such as building facades or mural paintings as well as the camera-captured document image since it employs the general features. The third rectification method is based on scene text detection algorithm, which is independent from the language model. The conventional methods assume that a character consists of a single connected component (CC) like English alphabet. However, this assumption is brittle in the Asian characters such as Korean, Chinese, and Japanese, where a single character consists of several CCs. Therefore, it is difficult to divide CCs into text lines without language model. To alleviate this problem, the proposed method clusters the candidate regions based on the similarity measure considering inter-character relation. The adjacency measure is trained on the data set labeled with the bounding box of text region. Non-text regions that remain after clustering are filtered out in text/non-text classification step. Final text regions are merged or divided into each text line considering the orientation and location. The detected text is rectified using the orientation of text-line and vertical strokes. The proposed method outperforms state-of-the-art algorithms in English as well as Asian characters in the extensive experiments.1 Introduction 1 1.1 Document rectification via text-line based optimization . . . . . . . 2 1.2 A unified approach of rectification and stitching for document images 4 1.3 Rectification via scene text detection . . . . . . . . . . . . . . . . . . 5 1.4 Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 Related work 9 2.1 Document rectification . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Document dewarping without text-lines . . . . . . . . . . . . 9 2.1.2 Document dewarping with text-lines . . . . . . . . . . . . . . 10 2.1.3 Text-block identification and text-line extraction . . . . . . . 11 2.2 Document stitching . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 Scene text detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3 Document rectification based on text-lines 15 3.1 Proposed approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1.1 Image acquisition model . . . . . . . . . . . . . . . . . . . . . 16 3.1.2 Proposed approach to document dewarping . . . . . . . . . . 18 3.2 Proposed cost function and its optimization . . . . . . . . . . . . . . 22 3.2.1 Design of Estr(·) . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2.2 Minimization of Estr(·) . . . . . . . . . . . . . . . . . . . . . 23 3.2.3 Alignment type classification . . . . . . . . . . . . . . . . . . 28 3.2.4 Design of Ealign(·) . . . . . . . . . . . . . . . . . . . . . . . . 29 3.2.5 Design of Espacing(·) . . . . . . . . . . . . . . . . . . . . . . . 31 3.3 Extension to unfolded book surfaces . . . . . . . . . . . . . . . . . . 32 3.4 Experimental result . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.4.1 Experiments on synthetic data . . . . . . . . . . . . . . . . . 36 3.4.2 Experiments on real images . . . . . . . . . . . . . . . . . . . 39 3.4.3 Comparison with existing methods . . . . . . . . . . . . . . . 43 3.4.4 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4 Document rectification based on feature detection 49 4.1 Proposed approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.2 Proposed cost function and its optimization . . . . . . . . . . . . . . 51 4.2.1 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.2.2 Homography between the i-th image and E . . . . . . . . . 52 4.2.3 Proposed cost function . . . . . . . . . . . . . . . . . . . . . . 53 4.2.4 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 4.2.5 Relation to the model in [17] . . . . . . . . . . . . . . . . . . 55 4.3 Post-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.3.1 Classification of two cases . . . . . . . . . . . . . . . . . . . . 56 4.3.2 Skew removal . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.4.1 Quantitative evaluation on metric reconstruction performance 57 4.4.2 Experiments on real images . . . . . . . . . . . . . . . . . . . 58 5 Scene text detection and rectification 67 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.1.1 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.1.2 Proposed approach . . . . . . . . . . . . . . . . . . . . . . . . 69 5.2 Candidate region detection . . . . . . . . . . . . . . . . . . . . . . . 70 5.2.1 CC extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 5.2.2 Computation of similarity between CCs . . . . . . . . . . . . 70 5.2.3 CC clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.3 Rectification of candidate region . . . . . . . . . . . . . . . . . . . . 73 5.4 Text/non-text classification . . . . . . . . . . . . . . . . . . . . . . . 76 5.5 Experimental result . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.5.1 Experimental results on ICDAR 2011 dataset . . . . . . . . . 80 5.5.2 Experimental results on the Asian character dataset . . . . . 80 6 Conclusion 83 Bibliography 87 Abstract (Korean) 97Docto