JigsawNet: Shredded Image Reassembly using Convolutional Neural Network and Loop-based Composition

This paper proposes a novel algorithm to reassemble an arbitrarily shredded image to its original status. Existing reassembly pipelines commonly consist of a local matching stage and a global compositions stage. In the local stage, a key challenge in fragment reassembly is to reliably compute and identify correct pairwise matching, for which most existing algorithms use handcrafted features, and hence, cannot reliably handle complicated puzzles. We build a deep convolutional neural network to detect the compatibility of a pairwise stitching, and use it to prune computed pairwise matches. To improve the network efficiency and accuracy, we transfer the calculation of CNN to the stitching region and apply a boost training strategy. In the global composition stage, we modify the commonly adopted greedy edge selection strategies to two new loop closure based searching algorithms. Extensive experiments show that our algorithm significantly outperforms existing methods on solving various puzzles, especially those challenging ones with many fragment pieces

Revisión de los métodos computerizados para la reconstrucción de fragmentos arqueológicos de cerámica

[ES] Las cerámicas son los hallazgos más numerosos encontrados en las excavaciones arqueológicas; a menudo se usan para obtener información sobre la historia, la economía y el arte de un sitio. Los arqueólogos rara vez encuentran jarrones completos; en general, están dañados y en fragmentos, a menudo mezclados con otros grupos de cerámica.El análisis y la reconstrucción de fragmentos se realiza por un operador experto mediante el uso del método manual tradicional. Los artículos revisados proporcionaron evidencias de que el método tradicional no es reproducible, no es repetible, consume mucho tiempo y sus resultados generan grandes incertidumbres. Con el objetivo de superar los límites anteriores, en los últimos años, los investigadores han realizado esfuerzos para desarrollar métodos informáticos que permitan el análisis de fragmentos arqueológicos de cerámica, todo ello destinado a su reconstrucción. Para contribuir a este campo de estudio, en este artículo, se presenta un análisis exhaustivo de las publicaciones disponibles más importantes hasta finales de 2019. Este estudio, centrado únicamente en fragmentos de cerámica, se realiza mediante la recopilación de artículos en inglés de la base de datos Scopus, utilizando las siguientes palabras clave: "métodos informáticos en arqueología", "arqueología 3D", "reconstrucción 3D", "reconocimiento y reconstrucción automática de características", "restauración de reliquias en forma de cerámica ". La lista se completa con referencias adicionales que se encuentran a través de la lectura de documentos seleccionados. Los 53 trabajos seleccionados se dividen en tres períodos de tiempo. Según una revisión detallada de los estudios realizados, los elementos clave de cada método analizado se enumeran en función de las herramientas de adquisición de datos, las características extraídas, los procesos de clasificación y las técnicas de correspondencia. Finalmente, para superar las brechas reales, se proponen algunas recomendaciones para futuras investigaciones.[EN] Potteries are the most numerous finds found in archaeological excavations; they are often used to get information about the history, economy, and art of a site. Archaeologists rarely find complete vases but, generally, damaged and in fragments, often mixed with other pottery groups. By using the traditional manual method, the analysis and reconstruction of sherds are performed by a skilled operator. Reviewed papers provided evidence that the traditional method is not reproducible, not repeatable, time-consuming and its results have great uncertainties. To overcome the aforementioned limits, in the last years, researchers have made efforts to develop computer-based methods for archaeological ceramic sherds analysis, aimed at their reconstruction. To contribute to this field of study, in this paper, a comprehensive analysis of the most important available publications until the end of 2019 is presented. This study, focused on pottery fragments only, is performed by collecting papers in English by the Scopus database using the following keywords: “computer methods in archaeology", "3D archaeology", "3D reconstruction", "automatic feature recognition and reconstruction", "restoration of pottery shape relics”. The list is completed by additional references found through the reading of selected papers. The 53 selected papers are divided into three periods of time. According to a detailed review of the performed studies, the key elements of each analyzed method are listed based on data acquisition tools, features extracted, classification processes, and matching techniques. Finally, to overcome the actual gaps some recommendations for future researches are proposed.Highlights:The traditional manual method for reassembling sherds is very time-consuming and costly; it also requires a great deal effort from skilled archaeologists in repetitive and routine activities.Computer-based methods for archaeological ceramic sherds reconstruction can help archaeologists in the above-mentioned repetitive and routine activities.In this paper, the state-of-the-art computer-based methods for archaeological ceramic sherds reconstruction are reviewed, and some recommendations for future researches are proposed.Eslami, D.; Di Angelo, L.; Di Stefano, P.; Pane, C. (2020). Review of computer-based methods for archaeological ceramic sherds reconstruction. 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In Proceedings of 9th Computer Vision Winter Workshop, (February), (pp. 31-40). Retrieved from https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/cvww041Karasik, A., & Smilansky, U. (2011). Computerized morphological classification of ceramics. Journal of Archaeological Science, 38(10), 2644-2657. https://doi.org/10.1016/j.jas.2011.05.023Kashihara, K. (2012). Three-dimensional reconstruction of artifacts based on a hybrid genetic algorithm. In IEEE International Conference on Systems, Man and Cybernetics, (pp. 900-905). https://doi.org/10.1109/ICSMC.2012.6377842Kashihara, K. (2017). An intelligent computer assistance system for artifact restoration based on genetic algorithms with plane image features. International Journal of Computational Intelligence and Applications, 16(3), 1-15. https://doi.org/10.1142/S1469026817500213Kleber, F., & Sablatnig, R. (2009). A survey of techniques for document and archaeology artifact reconstruction. 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In Proceedings of the 8th International Conference on Computer Graphics and Artificial Intelligence, Limoges, France, May 11-12, 2005, (pp. 135-147). https://semanticscholar.org/3c95/82c3e562b44e7d61dc0fd3487ea3dc977ff3Mara, H., Kampel, M., & Sablatnig, R. (2002). Preprocessing of 3D-Data for Classification of Archaeological Fragments in an Automated System. In Proceedings of the 26th Workshop of the Austrian Association for Pattern Recognition, Vision with Non-Traditional Sensors, (ÖAGM/AAPR), Graz, Austria, 10-11 September 2002, (pp. 257-264). https://doi.org/10.1.1.15.748Mara, H., & Sablatnig, R. (2006). The orientation of fragments of rotationally symmetrical 3D-shapes for archaeological documentation. In Proceedings - Third International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006, (June), (pp. 1064-1071). https://doi.org/10.1109/3DPVT.2006.105Melero, F. J., Torres, J. C., & Leon, A. (2003). On the interactive 3d reconstruction of Iberian vessels. 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Image Processing Applications in Real Life: 2D Fragmented Image and Document Reassembly and Frequency Division Multiplexed Imaging

In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied. In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the Fourier domain. Finally, a Texas Instruments digital micromirror device (DMD) based implementation of FDMI is presented and results are shown. Chapter 2 discusses the problem of image reassembly which is to restore an image back to its original form from its pieces after it has been fragmented due to different destructive reasons. We propose an efficient algorithm for 2D image fragment reassembly problem based on solving a variation of Longest Common Subsequence (LCS) problem. Our processing pipeline has three steps. First, the boundary of each fragment is extracted automatically; second, a novel boundary matching is performed by solving LCS to identify the best possible adjacency relationship among image fragment pairs; finally, a multi-piece global alignment is used to filter out incorrect pairwise matches and compose the final image. We perform experiments on complicated image fragment datasets and compare our results with existing methods to show the improved efficiency and robustness of our method. The problem of reassembling a hand-torn or machine-shredded document back to its original form is another useful version of the image reassembly problem. Reassembling a shredded document is different from reassembling an ordinary image because the geometric shape of fragments do not carry a lot of valuable information if the document has been machine-shredded rather than hand-torn. On the other hand, matching words and context can be used as an additional tool to help improve the task of reassembly. In the final chapter, document reassembly problem has been addressed through solving a graph optimization problem

Image Reassembly Combining Deep Learning and Shortest Path Problem

This paper addresses the problem of reassembling images from disjointed fragments. More specifically, given an unordered set of fragments, we aim at reassembling one or several possibly incomplete images. The main contributions of this work are: 1) several deep neural architectures to predict the relative position of image fragments that outperform the previous state of the art; 2) casting the reassembly problem into the shortest path in a graph problem for which we provide several construction algorithms depending on available information; 3) a new dataset of images taken from the Metropolitan Museum of Art (MET) dedicated to image reassembly for which we provide a clear setup and a strong baseline.Comment: ECCV 201

Optimization for automated assembly of puzzles

The puzzle assembly problem has many application areas such as restoration and reconstruction of archeological findings, repairing of broken objects, solving jigsaw type puzzles, molecular docking problem, etc. The puzzle pieces usually include not only geometrical shape information but also visual information such as texture, color, and continuity of lines. This paper presents a new approach to the puzzle assembly problem that is based on using textural features and geometrical constraints. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. Feature values are derived from these original and predicted images of pieces. An affinity measure of corresponding pieces is defined and alignment of the puzzle pieces is formulated as an optimization problem where the optimum assembly of the pieces is achieved by maximizing the total affinity measure. An fft based image registration technique is used to speed up the alignment of the pieces. Experimental results are presented on real and artificial data sets

Chapter Interactive Image Reconstruction from its Incomplete, Irregular and Imprecise Fragments

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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

An Investigation into the identification, reconstruction, and evidential value of thumbnail cache file fragments in unallocated space

©Cranfield UniversityThis thesis establishes the evidential value of thumbnail cache file fragments identified in unallocated space. A set of criteria to evaluate the evidential value of thumbnail cache artefacts were created by researching the evidential constraints present in Forensic Computing. The criteria were used to evaluate the evidential value of live system thumbnail caches and thumbnail cache file fragments identified in unallocated space. Thumbnail caches can contain visual thumbnails and associated metadata which may be useful to an analyst during an investigation; the information stored in the cache may provide information on the contents of files and any user or system behaviour which interacted with the file. There is a standard definition of the purpose of a thumbnail cache, but not the structure or implementation; this research has shown that this has led to some thumbnail caches storing a variety of other artefacts such as network place names. The growing interest in privacy and security has led to an increase in user’s attempting to remove evidence of their activities; information removed by the user may still be available in unallocated space. This research adapted popular methods for the identification of contiguous files to enable the identification of single cluster sized fragments in Windows 7, Ubuntu, and Kubuntu. Of the four methods tested, none were able to identify each of the classifications with no false positive results; this result led to the creation of a new approach which improved the identification of thumbnail cache file fragments. After the identification phase, further research was conducted into the reassembly of file fragments; this reassembly was based solely on the potential thumbnail cache file fragments and structural and syntactical information. In both the identification and reassembly phases of this research image only file fragments proved the most challenging resulting in a potential area of continued future research. Finally this research compared the evidential value of live system thumbnail caches with identified and reassembled fragments. It was determined that both types of thumbnail cache artefacts can provide unique information which may assist with a digital investigation. ii This research has produced a set of criteria for determining the evidential value of thumbnail cache artefacts; it has also identified the structure and related user and system behaviour of popular operating system thumbnail cache implementations. This research has also adapted contiguous file identification techniques to single fragment identification and has developed an improved method for thumbnail cache file fragment identification. Finally this research has produced a proof of concept software tool for the automated identification and reassembly of thumbnail cache file fragments