5225848
Towards an Automated Dental Identification System (ADIS)
This paper addresses the problem of developing an automated system for postmortem identification using dental records. The Automated Dental Identification System (ADIS) can be used by law enforcement agencies to locate missing persons using databases of dental x-rays. Currently, this search and identification process is carried out manually, which makes it very time-consuming and unreliable. In this paper, we propose architecture for ADIS, we define the functionality of its components, and we briefly describe some of the techniques used in realizing these components.
60842612
Tooth contour extraction for matching dental radiographs
In dental biometrics, the contours of teeth in dental radiographs are utilized for human identification. However, in many images, the contours of teeth are fuzzy and only partially visible. To extract the contours from these images, we propose a method based on the active contour models. A new dynamic energy is proposed for the directional snake to discriminate boundaries of adjacent teeth. Matching result shows the contours extracted with this method perform better than traditional methods.
6987127
3D model-assisted face recognition in video
Face recognition in video has gained wide attention as a covert method for surveillance to enhance security in a variety of application domains (e.g., airports). A video contains temporal information as well as multiple instances of a face, so it is expected to lead to better face recognition performance compared to still face images. However, faces appearing in a video have substantial variations in pose and lighting. These pose and lighting variations can be effectively modeled using 3D face models. Combining the advantages of 2D video and 3D face models, we propose a face recognition system that identifies faces in a video. The system utilizes the rich information in a video and overcomes the pose and lighting variations using 3D face model. The description of the proposed method and preliminary results are provided.
5510684
Robust motion-based image segmentation using fusion
To support real-time tracking of objects in video sequences, there has been considerable effort directed at developing optical flow and general motion-based image segmentation algorithms. The goal is to segment multiple moving objects in the image based on their relative motion. This task can be complicated by the presence of lighting variations. Furthermore, a combination of multiple motions and complex lighting effects can lead to dramatic image variations that may not be adequately accounted for by a single motion-based segmentation algorithm. We propose to fuse the results of multiple motion segmentation algorithms to improve the system robustness. Our approach uses the expectation maximization (EM) algorithm as a fusion engine. It also uses principal components analysis (PCA) to perform dimensionality reduction to improve the performance of the EM algorithm and reduce the processing burden. The performance of the proposed fusion algorithm has been demonstrated in the "smart airbag" application of monitoring occupants in a moving automobile to determine if they are too close to the instrument panel (airbag). Through fusion of the outputs of multiple algorithms we are able to reduce the percentage of pixels missed on the target by 35.
6295939
Dental Biometrics: Human Identification Using Dental Radiographs
The goal of forensic dentistry is to identify people based on their dental records, mainly as radiograph images. In this paper we attempt to set forth the foundations of a biometric system for semi-automatic processing and matching of dental images, with the final goal of human identification. Given a dental record, usually as a postmortem (PM) radiograph, we need to search the database of antemortem (AM) radiographs to determine the identity of the person associated with the PM image. We use a semi-automatic method to extract shapes of the teeth from the AM and PM radiographs, and find the affine transform that best fits the shapes in the PM image to those in the AM images. A ranking of matching scores is generated based on the distance between the AM and PM tooth shapes. Initial experimental results on a small database of radiographs indicate that matching dental images based on tooth shapes and their relative positions is a feasible method for human identification.
7988497
Matching of dental X-ray images for human identification
Forensic dentistry involves the identification of people based on their dental records, mainly available as radiograph images. Our goal is to automate this process using image processing and pattern recognition techniques. Given a postmortem radiograph, we search a database of antemortem radiographs in order to retrieve the closest match with respect to some salient features. In this paper, we use the contours of the teeth as the feature for matching. A semi-automatic contour extraction method is used to address the problem of fuzzy tooth contours caused by the poor image quality. The proposed method involves three stages: radiograph segmentation, pixel classification and contour matching. A probabilistic model is used to describe the distribution of object pixels in the image. Results of retrievals on a database of over 100 images are encouraging.
6650752
Using Content-Based and Link-Based Analysis in Building Vertical Search Engines
This paper reports our research in the Web page filtering process in specialized search engine development. We propose a machine-learning-based approach that combines Web content analysis and Web structure analysis. Instead of a bag of words, each Web page is represented by a set of content-based and link-based features, which can be used as the input for various machine learning algorithms. The proposed approach was implemented using both a feedforward/backpropagation neural network and a support vector machine. An evaluation study was conducted and showed that the proposed approaches performed better than the benchmark approaches.
8882088
Design of Nearest Neighbor Classifiers Using an Intelligent Multi-objective Evolutionary Algorithm
The goal of designing optimal nearest neighbor classifiers is to maximize classification accuracy while minimizing the sizes of both reference and feature sets. A usual way is to adaptively weight the three objectives as an objective function and then use a single-objective optimization method for achieving this goal. This paper proposes a multi-objective approach to cope with the weight tuning problem for practitioners. A novel intelligent multi-objective evolutionary algorithm IMOEA is utilized to simultaneously edit compact reference and feature sets for nearest neighbor classification. Two comparison studies are designed to evaluate performance of the proposed approach. It is shown empirically that the IMOEA-designed classifiers have high classification accuracy and small sizes of reference and feature sets. Moreover, IMOEA can provide a set of good solutions for practitioners to choose from in a single run. The simulation results indicate that the IMOEA-based approach is an expedient method to design nearest neighbor classifiers, compared with an existing single- objective approach.
18485323
Using Coplink to Analyze Criminal-Justice Data
The paper discusses the Coplink system. The system applies a concept space-a statistics-based, algorithmic technique that identifies relationships between suspects, victims, and other pertinent data-to accelerate criminal investigations and enhance law enforcement efforts. The Coplink concept space application, which began as a research project, has evolved into a real-time system being used in everyday police work. Coplink CS has been successfully deployed at the Tucson Police Department, where crime analysts, officers, detectives, and sergeants from 16 departmental units use the technology voluntarily as part of their daily investigative routine.
9059456
Model Checking One Million Lines of C Code
Implementation bugs in security-critical software are pervasive. Several authors have previously suggested model checking as a promising means to detect improper use of system interfaces and thereby detect a broad class of security vulnerabilities. In this paper, we report on our practical experience using MOPS, a tool for software model checking security-critical applications. As examples of security vulnerabilities that can be analyzed using model checking, we pick five important classes of vulnerabilities and show how to codify them as temporal safety properties, and then we describe the results of checking them on several significant Unix applications using MOPS. After analyzing over one million lines of code, we found more than a dozen new security weaknesses in important, widely-deployed applications. This demonstrates for the first time that model checking is practical and useful for detecting security weaknesses at large scale in real,
1165445
Physical planning of on-chip interconnect architectures
Interconnect architecture plays an important role in determining the throughput of meshed communication structures. We assume a mesh structure with uniform communication demand for communication. A multi-commodity flow (MCF) model is proposed to find the throughput for several different routing architectures. The experimental results reveal several trends: 1. The throughput is limited by the capacity of the middle row and column in the mesh, simply enlarging the congested channel cannot produce better throughput. A flexible chip shape provides around 30% throughput improvement over a square chip of equal area. 2. A 45-degree mesh allows 17% throughput improvement over 90-degree mesh and a 90-degree and 45-degree mixed mesh provides 30% throughput improvement. 3. To achieve maximum throughput on a mixed Manhattan and diagonal interconnect architecture, the best ratio of the capacity for diagonal routing layers and the capacity for Manhattan routing layers is 5.6. 4. Incorporating a simplified via model, interleaving diagonal routing layers and Manhattan routing layer is the best way to organize the wiring directions on different layers.