Towards a unified framework for identity documents analysis and recognition

Identity documents recognition is far beyond classical optical character recognition problems. Automated ID document recognition systems are tasked not only with the extraction of editable and transferable data but with performing identity validation and preventing fraud, with an increasingly high cost of error. A significant amount of research is directed to the creation of ID analysis systems with a specific focus for a subset of document types, or a particular mode of image acquisition, however, one of the challenges of the modern world is an increasing demand for identity document recognition from a wide variety of image sources, such as scans, photos, or video frames, as well as in a variety of virtually uncontrolled capturing conditions. In this paper, we describe the scope and context of identity document analysis and recognition problem and its challenges; analyze the existing works on implementing ID document recognition systems; and set a task to construct a unified framework for identity document recognition, which would be applicable for different types of image sources and capturing conditions, as well as scalable enough to support large number of identity document types. The aim of the presented framework is to serve as a basis for developing new methods and algorithms for ID document recognition, as well as for far more heavy challenges of identity document forensics, fully automated personal authentication and fraud prevention.This work was partially supported by the Russian Foundation for Basic Research (Project No. 18-29-03085 and 19-29-09055)

A non-destructive technique for health assessment of fire-damaged concrete elements using terrestrial laser scanning

Concrete structures are routinely monitored to detect changes in their characteristics in the field of engineering surveying and other disciplines such as structural and civil engineering. There is growing demand for the development of reliable Non-Destructive Testing (NDT) techniques for concrete structures in the assessment of the deteriorating condition of infrastructures or in an event of fire-damaged structures. In this paper, the feasibility of using Terrestrial Laser Scanning (TLS) technology for change detection and assessment of fire-damaged concrete has been investigated through measurements and analysis of laboratory size concrete specimens that underwent heating up to 1000°C. The TLS technique employed in detecting fire-damaged concrete involved modelling and analysis of the TLS intensity returns as well as RGB image analysis. The results obtained clearly demonstrate the feasibility of using TLS to detect fire-damaged concrete. Although the laser scanners used in the study have different wavelengths, the results obtained in both cases are promising for a detection technique of fire-damaged concrete structures

Automated Fingerprint Identification System: with and without the Possibility of Correction of a Digitalised Image

According to the fact that systems for automatic processing of biometric data are constantly advancing in terms of speed and reliability, as well as in terms of adding new processing capabilities, the question of choosing the appropriate system becomes more important. In this paper the idea is to present the technical and technological solutions of the Automated Fingerprint Identification System with different operating principles, with and without the possibility of correction or coding of a digitized image. Comparisons of different systems were performed in test and production environments. The test database with 10 000 records and about half a million records of dactyloscoped persons in the production of database for testing the performance of search was used. The results have shown that there exists a statistically significant difference (p < 0.001) between examined systems in face fingerprint search according to latent fingerprint databases (which means indirect verification). In the production environment, it was found that there exists statistically significant difference (p < 0.001) in the direct and indirect verification showing advantages and disadvantages of the compared systems

Extracting Handwritten Annotations from Printed Documents Via Infrared Scanning

Despite ever improving digital ink and paper solutions, many people still prefer printing out documents for close reading, proofreading, or filling out forms. However, in order to incorporate paper-based annotations into digital workflows, handwritten text and markings need to be extracted. Common computer-vision and machine-learning approaches require extensive sets of training data or a clean digital version of the document. We propose a simple method for extracting handwritten annotations from laser-printed documents using multispectral imaging. While black toner absorbs infrared light, most inks are invisible in the infrared spectrum. We modified an off-the-shelf flatbed scanner by adding a switchable infrared LED to its light guide. By subtracting an infrared scan from a color scan, handwritten text and highlighting can be extracted and added to a PDF version. Initial experiments show accurate results with high quality on a test data set of 93 annotated pages. Thus, infrared scanning seems like a promising building block for integrating paper-based and digital annotation practices