Enhancing gifts-in-kind assessment and processing with digital photography

Purpose: This paper sets out to explore the potential benefits of using digital photography in the evaluation of prospective donations of book collections. Design/methodology/approach: The paper describes a methodology for creating a collection of images to preserve bibliographic information from large book donations where time and distance restrictions limit the ability to carry out a thorough investigation on-site. This image collection will assist in the initial assessment of the collection's suitability for acceptance, documentation and creation of a gift list. Findings: Using digital photography allows for relatively quick and comprehensive documentation to aid in the evaluation of large potential gift-inkind donations. Additional benefits realized from acquiring digital images may include automation of gift list creation, publicity for the newly acquired collection, and enhancing exhibitions. This methodology utilizes readily available and affordable equipment that will likely be well within the resources of most libraries. Originality/value: This paper offers practical advice on employing current and emerging digital technologies to assess and enhance gift-in-kind donations

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

Valorisation of history and landscape for promoting the memory of WWI

10 p.In recent years many activities were conducted to commemorate the 100th Anniversary of the FirstWorld War (WWI) outbreak. Among these, the valorisation of history and landscape (VAST) project(http://vast.fbk.eu) was part of the initiatives promoted by the Autonomous Province of Trento (Italy)as a tribute to WWI events in the region. The project was primarily aimed to document and promote,through 3D digitization approaches, ICT technologies and communication material, the memory of sites,theatre of the world conflict. The Trento’s area was under the Austro-Hungarian Empire until the end ofWWI and on the border with the Italian Kingdom. The area represented a crucial and bloody war frontbetween the Austrian and Italian territories. It was thus constellated of military fortresses, trenches andtunnels, most of them now ruined and at risk to slowly disappear. 3D surveying and modelling techniqueswere exploited to produce 3D digital models of structures and objects, along with virtual tours, dissem-ination material and a WebGIS of the area. All the products are now used for restoration, valorisation,educational and communication purposesS

Readability Enhancement and Palimpsest Decipherment of Historical Manuscripts

This paper presents image acquisition and readability enhancement techniques for historical manuscripts developed in the interdisciplinary project “The Enigma of the Sinaitic Glagolitic Tradition” (Sinai II Project).1 We are mainly dealing with parchment documents originating from the 10th to the 12th centuries from St. Cather- ine’s Monastery on Mount Sinai. Their contents are being analyzed, fully or partly transcribed and edited in the course of the project. For comparison also other mss. are taken into consideration. The main challenge derives from the fact that some of the manuscripts are in a bad condition due to various damages, e.g. mold, washed out or faded text, etc. or contain palimpsest (=overwritten) parts. Therefore, the manuscripts investigated are imaged with a portable multispectral imaging system. This non-invasive conservation technique has proven extremely useful for the exami- nation and reconstruction of vanished text areas and erased or washed o palimpsest texts. Compared to regular white light, the illumination with speci c wavelengths highlights particular details of the documents, i.e. the writing and writing material, ruling, and underwritten text. In order to further enhance the contrast of the de- graded writings, several Blind Source Separation techniques are applied onto the multispectral images, including Principal Component Analysis (PCA), Independent Component Analysis (ICA) and others. Furthermore, this paper reports on other latest developments in the Sinai II Project, i.e. Document Image Dewarping, Automatic Layout Analysis, the recent result of another project related to our work: the image processing tool Paleo Toolbar, and the launch of the series Glagolitica Sinaitica

LiDARPheno: A Low-Cost LiDAR-based 3D Scanning System for Plant Morphological Trait Characterization

The ever-growing world population brings the challenge for food security in the current world. The gene modification tools have opened a new era for fast-paced research on new crop identification and development. However, the bottleneck in the plant phenotyping technology restricts the alignment in Geno-pheno development as phenotyping is the key for the identification of potential crop for improved yield and resistance to the changing environment. Various attempts to making the plant phenotyping a “high-throughput” have been made while utilizing the existing sensors and technology. However, the demand for ‘good’ phenotypic information for linkage to the genome in understanding the gene-environment interactions is still a bottleneck in the plant phenotyping technologies. Moreover, the available technologies and instruments are inaccessible, expensive and sometimes bulky. This thesis work attempts to address some of the critical problems, such as exploration and development of a low-cost LiDAR-based platform for phenotyping the plants in-lab and in-field. A low-cost LiDAR-based system design, LiDARPheno, is introduced in this thesis work to assess the feasibility of the inexpensive LiDAR sensor in the leaf trait (length, width, and area) extraction. A detailed design of the LiDARPheno, based on low-cost and off-the-shelf components and modules, is presented. Moreover, the design of the firmware to control the hardware setup of the system and the user-level python-based script for data acquisition is proposed. The software part of the system utilizes the publicly available libraries and Application Programming Interfaces (APIs), making it easy to implement the system by a non-technical user. The LiDAR data analysis methods are presented, and algorithms for processing the data and extracting the leaf traits are developed. The processing includes conversion, cleaning/filtering, segmentation and trait extraction from the LiDAR data. Experiments on indoor plants and canola plants were performed for the development and validation of the methods for estimation of the leaf traits. The results of the LiDARPheno based trait extraction are compared with the SICK LMS400 (a commercial 2D LiDAR) to assess the performance of the developed system. Experimental results show a fair agreement between the developed system and a commercial LiDAR system. Moreover, the results are compared with the acquired ground truth as well as the commercial LiDAR system. The LiDARPheno can provide access to the inexpensive LiDAR-based scanning and open the opportunities for future exploration

Enhancing Real-time Embedded Image Processing Robustness on Reconfigurable Devices for Critical Applications

Nowadays, image processing is increasingly used in several application fields, such as biomedical, aerospace, or automotive. Within these fields, image processing is used to serve both non-critical and critical tasks. As example, in automotive, cameras are becoming key sensors in increasing car safety, driving assistance and driving comfort. They have been employed for infotainment (non-critical), as well as for some driver assistance tasks (critical), such as Forward Collision Avoidance, Intelligent Speed Control, or Pedestrian Detection. The complexity of these algorithms brings a challenge in real-time image processing systems, requiring high computing capacity, usually not available in processors for embedded systems. Hardware acceleration is therefore crucial, and devices such as Field Programmable Gate Arrays (FPGAs) best fit the growing demand of computational capabilities. These devices can assist embedded processors by significantly speeding-up computationally intensive software algorithms. Moreover, critical applications introduce strict requirements not only from the real-time constraints, but also from the device reliability and algorithm robustness points of view. Technology scaling is highlighting reliability problems related to aging phenomena, and to the increasing sensitivity of digital devices to external radiation events that can cause transient or even permanent faults. These faults can lead to wrong information processed or, in the worst case, to a dangerous system failure. In this context, the reconfigurable nature of FPGA devices can be exploited to increase the system reliability and robustness by leveraging Dynamic Partial Reconfiguration features. The research work presented in this thesis focuses on the development of techniques for implementing efficient and robust real-time embedded image processing hardware accelerators and systems for mission-critical applications. Three main challenges have been faced and will be discussed, along with proposed solutions, throughout the thesis: (i) achieving real-time performances, (ii) enhancing algorithm robustness, and (iii) increasing overall system's dependability. In order to ensure real-time performances, efficient FPGA-based hardware accelerators implementing selected image processing algorithms have been developed. Functionalities offered by the target technology, and algorithm's characteristics have been constantly taken into account while designing such accelerators, in order to efficiently tailor algorithm's operations to available hardware resources. On the other hand, the key idea for increasing image processing algorithms' robustness is to introduce self-adaptivity features at algorithm level, in order to maintain constant, or improve, the quality of results for a wide range of input conditions, that are not always fully predictable at design-time (e.g., noise level variations). This has been accomplished by measuring at run-time some characteristics of the input images, and then tuning the algorithm parameters based on such estimations. Dynamic reconfiguration features of modern reconfigurable FPGA have been extensively exploited in order to integrate run-time adaptivity into the designed hardware accelerators. Tools and methodologies have been also developed in order to increase the overall system dependability during reconfiguration processes, thus providing safe run-time adaptation mechanisms. In addition, taking into account the target technology and the environments in which the developed hardware accelerators and systems may be employed, dependability issues have been analyzed, leading to the development of a platform for quickly assessing the reliability and characterizing the behavior of hardware accelerators implemented on reconfigurable FPGAs when they are affected by such faults

Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review

In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings