A Survey of the methods on fingerprint orientation field estimation

Fingerprint orientation field (FOF) estimation plays a key role in enhancing the performance of the automated fingerprint identification system (AFIS): Accurate estimation of FOF can evidently improve the performance of AFIS. However, despite the enormous attention on the FOF estimation research in the past decades, the accurate estimation of FOFs, especially for poor-quality fingerprints, still remains a challenging task. In this paper, we devote to review and categorization of the large number of FOF estimation methods proposed in the specialized literature, with particular attention to the most recent work in this area. Broadly speaking, the existing FOF estimation methods can be grouped into three categories: gradient-based methods, mathematical models-based methods, and learning-based methods. Identifying and explaining the advantages and limitations of these FOF estimation methods is of fundamental importance for fingerprint identification, because only a full understanding of the nature of these methods can shed light on the most essential issues for FOF estimation. In this paper, we make a comprehensive discussion and analysis of these methods concerning their advantages and limitations. We have also conducted experiments using publically available competition dataset to effectively compare the performance of the most relevant algorithms and methods

Image enhancement and segmentation on simultaneous latent fingerprint detection

A simultaneous latent fingerprint (SLF) image consists of multi-print of individual fingerprints that is lifted from a surface, typically at the crime scenes. Due to the nature and the poor quality of latent fingerprint image, segmentation becomes an important and very challenging task. This thesis presents an algorithm to segment individual fingerprints for SLF image. The algorithm aim to separate the fingerprint region of interest from image background, which identifies the distal phalanx portion of each finger that appears in SLF image. The algorithm utilizes ridge orientation and frequency features based on block-wise pixels. A combination of Gabor Filter and Fourier transform is implemented in the normalization stage. In the pre-processing stage, a modified version of Histogram equalization is proposed known as Alteration Histogram Equalization (AltHE). Sliding windows are applied to create bounding boxes in order to find out the distal phalanges region at the segmentation stage. To verify the capability of the proposed segmentation algorithm, the segmentation results is evaluated in two aspects: a comparison with the ground truth foreground and matching performance based on segmented region. The ground truth foreground refers to the manual mark up region of interest area. In order to evaluate the performance of this method, experiments are performed on the Indian Institute of Information Technology Database- Simultaneous Latent Fingerprint (IIITD-SLF). Using the proposed algorithm, the segmented images were supplied as the input image for the matching process via a state art of matcher, VeriFinger SDK. Segmentation of 240 images is performed and compared with manual segmentation methods. The results show that the proposed algorithm achieves a correct segmentation of 77.5% of the SLF images under test

Contextual biometric watermarking of fingerprint images

This research presents contextual digital watermarking techniques using face and demographic text data as multiple watermarks for protecting the evidentiary integrity of fingerprint image. The proposed techniques embed the watermarks into selected regions of fingerprint image in MDCT and DWT domains. A general image watermarking algorithm is developed to investigate the application of MDCT in the elimination of blocking artifacts. The application of MDCT has improved the performance of the watermarking technique compared to DCT. Experimental results show that modifications to fingerprint image are visually imperceptible and maintain the minutiae detail. The integrity of the fingerprint image is verified through high matching score obtained from the AFIS system. There is also a high degree of correlation between the embedded and extracted watermarks. The degree of similarity is computed using pixel-based metrics and human visual system metrics. It is useful for personal identification and establishing digital chain of custody. The results also show that the proposed watermarking technique is resilient to common image modifications that occur during electronic fingerprint transmission

Chemical Processing of Fingerprints on Thermal Paper

This research seeks to determine how well muriatic acid and acetic acid fuming develop the thermal side of thermal paper using aged prints. Additionally, the research seeks to determine how well ninhydrin develops the paper side of thermal paper using aged prints after exposure to the fuming. Twenty-four random individuals placed a total of thirty sets of fingerprints per person on thermal paper over a 10-day period. Each set of fingerprints consisted of three fingerprints on the thermal side of paper and three fingerprints on the nonthermal side of paper. During the 30 to 40-day time period, however, more specifically around the 35-day time period, the fingerprint quality diminishes to a point of not being able to process fingerprints adequately

The use of Automated Fingerprint Identification System in identifying fraudulent voters’ registration in Lesotho

The research was prompted by constant criticism of the Independent Electoral Commission (IEC) because of its poor voter registration and voters’ roll. Free and fair elections are the strong arm of democracy. The identified research problem was investigated by means of qualitative research. A thorough literature study from various sources of information, a case file analysis and structured interviews were used to gather the required data. The interviews were conducted with fingerprint experts, a data processor and constituency electoral assistants from the Lesotho Mounted Police Service, the National Identity and Civil Registry at the Ministry of Home Affairs and the IEC respectively. It was found that using fingerprints and the Automated Fingerprint Identification System (AFIS) can assist in investigations and in combating voter’s fraud, as fingerprints are unique. AFIS can be utilised for various purposes by institutions in the private and public sectors. Like any apparatus, AFIS has its own strengths and weaknesses.Criminology and Security ScienceM. Tech. (Forensic investigation

Impact of humidity on latent print processing and recovery

The goal of this study was to determine if environmental factors impact the quality of detail in latent prints on non-porous and porous surfaces. Specifically, this study focused on how humidity impacts latent print processing, development, and analysis on tile and paper. Latent prints are prints deposited on surfaces in sweat (James, Nordby & Bell, 2014). As humidity is water vapor in the air, it is expected that increased humidity would have a noticeable impact on the quality of latent prints. To date, no research has been conducted comparing how humidity impacts latent prints on porous and non-porous surfaces at consistent temperatures. In this study, latent prints were deposited on a non-porous surface (white tile) and a porous surface (paper) and subjected to 30%, 50% and 90% humidity at a consistent temperature range (70-74 degrees Fahrenheit) to assess if humidity causes a noticeable change in the quality of latent prints. Once collected, prints were uploaded into the Automated Fingerprint Identification System (AFIS), which was set to automatically mark minutiae. Minutiae were then edited by an experienced latent fingerprint examiner to ensure accuracy. The edited minutiae count generated from AFIS was used to determine what category each print fell under: low quality (0-6 minutiae), moderate quality (7-12 minutiae), or high quality (13 and above minutiae). Multiple statistical tests were performed to determine statistical significance between different variables. This included comparing tracked humidities, tracked temperature ranges, overall minutiae count between humidities, and change in minutiae count over time. Based on the results, humidity did appear to have an impact on the quality of the prints over time for both surfaces, porous and non-porous. Overall, quality decreased with increased levels of humidity. At each humidity, a decrease in quality was also observed over time. The only prints that deviated from this were the prints on the tile at 90% humidity tile. These prints stayed at a consistent low quality. This leads to the conclusion that prints recovered on white tile with black powder and prints recovered on paper with ninhydrin decrease in quality with increased levels of humidity and also decrease over time at set humidities

A Translation And Rotation Independent Fingerprint Identification Approach

This thesis describes a new approach for fingerprint identification that will be shift and rotation independent. Detailed descriptions of directional filtering, foreground and background segmentation, feature extraction, and matching based on structural correlation are the main topics of this thesis. The fingerprint identification system consists of image preprocessing, feature extraction, and matching which run on a PC platform. The preprocessing step includes histogram equalization, block-based directional filtering, thinning, and adaptive thresholding to enhance the original images for successful feature extraction. The features extracted will be stored in the database for matching. The matching algorithm presented is a modification and improvement of the structural approach. A two-step process of local feature matching and global feature matching guarantees the correct matching results

Mitigating Sensor and Acquisition Method-Dependence of Fingerprint Presentation Attack Detection Systems by Exploiting Data from Multiple Devices

The problem of interoperability is still open in fingerprint presentation attack detection (PAD) systems. This involves costs for designers and manufacturers who intend to change sensors of personal recognition systems or design multi-sensor systems, because they need to obtain sensor-specific spoofs and retrain the system. The solutions proposed in the state of the art to mitigate the problem still require data from the target sensor and are therefore not exempt from the problem of obtaining new data. In this paper, we provide insights for the design of PAD systems thanks to an overview of an interoperability analysis on modern systems: hand-crafted, deep-learning-based, and hybrid. We investigated realistic use cases to determine the pros and cons of training with data from multiple sensors compared to training with single sensor data, and drafted the main guidelines to follow for deciding the most convenient PAD design technique depending on the intended use of the fingerprint identification/authentication system