887 research outputs found
Documentation and analysis of plastic fingerprint impressions involving contactless three-dimensional surface scanning
Fingerprint impressions are frequently encountered during the investigation of crime scenes, and may establish a crucial linkage between the suspect and the crime scene. Plastic fingerprint impressions found at crime scenes are often transient and delicate, leaving photography the sole means of documentation. A traditional photography approach can be inadequate in documenting impressions that contain three-dimensional (3D) details due to the limitations of camera and lighting conditions on scene. In this study, 3D scanning was proposed as a novel method for the documentation of plastic fingerprints. Structured-light 3D scanning (SLS) captures the distortion of projected light patterns on the subject to obtain its 3D profile, which allows fast acquisition of the complete 3D geometric information of the surface. The contactless operation of SLS also eliminates the risk of destroying fragile evidence, making it a sound choice for forensic applications.
In this study, the feasibility of 3D scanning of plastic fingerprint impressions was evaluated and compared with traditional photography regarding the quantity and quality of perceptible friction ridge features. Attempts were made to develop a procedure to extract curvature features from 3D scanned fingerprints and flatten the friction ridge features into two-dimensional (2D) images to allow direct comparison with the traditional photography method in the CSIpixÂź Matcher and NFIQ 2.0 software. One of the developed methods (3DR) utilizing a discrete geometry operator and convexity features outperformed traditional photography, both in minutiae count and match quality, while traditional photography could not always capture enough high-quality minutiae for comparisons, even after digital enhancement. The reproducibility of the 3D scanning process was evaluated using 3D point cloud statistics. The pair-wise mean distance and standard deviation were calculated for four levels of comparisons with theoretically increasing disparity, including pairs of scans of the same impressions. The results showed minimal shape deviation from scan to scan for the same impression, but high variations for different impressions
Personal Identification using the Distance and Triangle between the Metacarpophalangeal Joints
Personal identification using the distance among the metacarpophalangeal joints (MCPs) was presented in this study. The system was developed to specify the dorsal hand patterns. Firstly, the dorsal hand images were taken for the subjects via an infrared camera. Secondly, the dorsal hand images were converted to grayscale and binary images using image processing techniques. After that, the distance of the MCPs was measured by various the dorsal hand images including index to middle, middle to ring, ring to little, and index to little of the dorsal hand. In addition, the triangle areas between index to middle, middle to ring, ring to little, and index to little of the dorsal hand were used to specify the dorsal hand patterns. The result of the distance and the triangle area of the MCPS can be used to identify a person because of the difference of distance and the triangle area of the MCPs of each person.
A hyprid technique for human footprint recognition
Biometrics has concerned a great care recently due to its important in the life that starts from civil applications to security and recently terrorism. A Footprint recognition is one of the personal identifications based on biometric measurements. The aim of this research is to design a proper and reliable biometric system for human footprint recognition named (FRBS) that stands for Footprint Recognition Biometric System. In addition, to construct a human footprint database which it is very helpful for various use in scientific application e.g. for authentication. There exist many biometrics databases for other identity but very rare for footprint. As well as the existing one are very limited. This paper presents a robust hyprid techniques which merges between Image Processing with Artificial Intelligent technique via Ant Colony Optimization (ACO) to recognize human footprint. (ACO) plays the essential role that rise the performance and the quality of the results in the biometric system via feature selection. The set of the selected features was treated as exploratory information, and selects the optimum feature set in standings of feature set size. Life RGB footprint images from nine persons with ten images per person constructed from life visual dataset. At first, the visual dataset was pre-processed operations. Each resultant image detects footprint that is cropped to portions represented by three blocks. The first block is for fingers, the second block refers to the center of the foot and the last one determines the heel. Then features were extracted from each image and stored in Excel file to be entered to Ant Colony Optimization Algorithm. The experimental outcomes of the system show that the proposed algorithm evaluates optimal results with smaller feature set comparing with other algorithms. Experimental outcomes show that our algorithm obtains an efficient and accurate result about 100% accuracy in comparison with other researches on the same field
Advances in Image Processing, Analysis and Recognition Technology
For many decades, researchers have been trying to make computersâ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches
Evaluation of Single and Dual image Object Detection through Image Segmentation Using ResNet18 in Robotic Vision Applications
This study presents a method for enhancing the accuracy of object detection in industrial automation applications using ResNet18-based image segmentation. The objective is to extract object images from the background image accurately and efficiently. The study includes three experiments, RGB to grayscale conversion, single image processing, and dual image processing. The results of the experiments show that dual image processing is superior to both RGB to grayscale conversion and single image processing techniques in accurately identifying object edges, determining CG values, and cutting background images and gripper heads. The program achieved a 100% success rate for objects located in the workpiece tray, while also identifying the color and shape of the object using ResNet-18. However, single image processing may have advantages in certain scenarios with sufficient image information and favorable lighting conditions. Both methods have limitations, and future research could focus on further improvements and optimization of these methods, including separating objects into boxes of each type and converting image coordinate data into robot working area coordinates. Overall, this study provides valuable insights into the strengths and limitations of different object recognition techniques for industrial automation applications
Optical Methods in Sensing and Imaging for Medical and Biological Applications
The recent advances in optical sources and detectors have opened up new opportunities for sensing and imaging techniques which can be successfully used in biomedical and healthcare applications. This book, entitled âOptical Methods in Sensing and Imaging for Medical and Biological Applicationsâ, focuses on various aspects of the research and development related to these areas. The book will be a valuable source of information presenting the recent advances in optical methods and novel techniques, as well as their applications in the fields of biomedicine and healthcare, to anyone interested in this subject
A novel expert system for objective masticatory efficiency assessment
Most of the tools and diagnosis models of Masticatory Efficiency (ME) are not well documented or severely limited to simple image processing approaches. This study presents a novel expert system for ME assessment based on automatic recognition of mixture patterns of masticated two-coloured chewing gums using a combination of computational intelligence and image processing techniques. The hypotheses tested were that the proposed system could accurately relate specimens to the number of chewing cycles, and that it could identify differences between the mixture patterns of edentulous individuals prior and after complete denture treatment. This study enrolled 80 fully-dentate adults (41 females and 39 males, 25 ± 5 years of age) as the reference population; and 40 edentulous adults (21 females and 19 males, 72 ± 8.9 years of age) for the testing group. The system was calibrated using the features extracted from 400 samples covering 0, 10, 15, and 20 chewing cycles. The calibrated system was used to automatically analyse and classify a set of 160 specimens retrieved from individuals in the testing group in two appointments. The ME was then computed as the predicted number of chewing strokes that a healthy reference individual would need to achieve a similar degree of mixture measured against the real number of cycles applied to the specimen. The trained classifier obtained a Mathews Correlation Coefficient score of 0.97. ME measurements showed almost perfect agreement considering pre- and post-treatment appointments separately (Îș â„ 0.95). Wilcoxon signed-rank test showed that a complete denture treatment for edentulous patients elicited a statistically significant increase in the ME measurements (Z = -2.31, p < 0.01). We conclude that the proposed expert system proved able and reliable to accurately identify patterns in mixture and provided useful ME measurements.This work was funded by the Secretaria Nacional de EducaciĂłn, Ciencia y TeconologĂa (SENESCYT) of the Government of Ecuador, with budget allocation No. 0099-SPP, http://www.educacionsuperior.gob.ec
Biometrics
Biometrics-Unique and Diverse Applications in Nature, Science, and Technology provides a unique sampling of the diverse ways in which biometrics is integrated into our lives and our technology. From time immemorial, we as humans have been intrigued by, perplexed by, and entertained by observing and analyzing ourselves and the natural world around us. Science and technology have evolved to a point where we can empirically record a measure of a biological or behavioral feature and use it for recognizing patterns, trends, and or discrete phenomena, such as individuals' and this is what biometrics is all about. Understanding some of the ways in which we use biometrics and for what specific purposes is what this book is all about
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