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Classification and numbering of dental radiographs for an automated human identification system

Telkomnika 2012年第1期10卷 137-146页

作者： Yuniarti, Anny Nugroho, Anindhita Sigit Amaliah, Bilqis Arifin, Agus Zainal Laboratory of Vision and Image Processing Department of Informatics Faculty of Information Technology Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia

Dental based human identification is commonly used in forensic. In a case of large scale investigation, manual identification needs a large amount of time. In this paper, we developed an automated human identification system based on dental radiographs. The system developed has two main stages. The first stage is to arrange a database consisting of labeled dental radiographs. The second stage is the searching process in the database in order to retrieve the identification result. Both stages use a number of image processing techniques, classification methods, and a numbering system in order to generate dental radiograph's features and patterns. The first technique is preprocessing which includes image enhancement and binarization, single tooth extraction, and feature extraction. Next, we performed dental classification process which aims to classify the extracted tooth into molar or premolar using the binary support vector machine method. After that, a numbering process is executed in accordance with molar and premolar pattern obtained in the previous process. Our experiments using 16 dental radiographs that consist of 6 bitewing radiographs and 10 panoramic radiographs, 119 teeth objects in total, has shown good performance of classification. The accuracy value of dental pattern classification and dental numbering system are 91.6 % and 81.5% respectively. © 2012 Universitas Ahmad Dahlan.

关键词： Numbering systems

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Three-dimensional image analysis and display by space-scale matching of cross sections

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Journal of the Optical Society of America A: Optics and image Science, and vision 1989年第6期6卷 890-899页

作者： Algazi, V.R. Reutter, B.W. van Warmerdam, W.L.G. Liu, C.C. Graphics Image and Vision Engineering Research Laboratory Center for Image Processing and Integrated Computing University of California Davis CA 95616 United States

We present a framework and a set of techniques for the analysis and display of three-dimensional experimental data or images. We assume that the data are available in the form of two-dimensional cross sections of the three dimensional data set. We describe our approach, which has for goals to extract significant information from the three-dimensional data set and to display this information as objects that can be manipulated in three-dimensional space. The high-contrast transitions of two-dimensional cross sections are extracted first;they define a set of contours to be matched from cross section to cross section. This matching is performed by space-scale analysis of the orientation of contours on adjacent cross sections. By modeling the contours as B splines, we then make use of three-dimensional B-spline patches to generate significant surfaces that can be displayed, rendered, and rotated with standard computer graphics techniques and specialized processors. © 1989 Optical Society of America.

关键词： Computed tomography Computer simulation image analysis image processing Imaging systems Three dimensional imaging

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Cerebrovascular segmentation for MRA data using level sets

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International Congress Series 2003年第C期1256卷 246-252页

作者： Hassan, Hossam Farag, Aly A Computer Vision Image Processing Laboratory University of Louisville Lutz Hall Louisville KY 40292 United States

In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Phase Contrast Magnetic Resonance Angiography, “PCMRA”. Classification model finds an optimal partition of homogeneous classes with regular interfaces. Regions and their interfaces are represented by level set functions. The algorithm initializes level sets in each image slice using automatic seed initialization and then iteratively, each level set approaches the steady state and contains the vessel or non-vessel area. The results are validated using a phantom that simulates the “PCMRA”. The approach is fast and accurate. Results on various cases demonstrate the accuracy of the approach. © 2003, Elsevier Science B.V. All rights reserved.

关键词： Level set segmentation PCMRA PDE Seed initialization Vascular tree

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Parameter estimation in Gibbs-Markov image models

Parameter estimation in Gibbs-Markov image models

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6th International Conference on Information Fusion, FUSION 2003

作者： El-Baz, Ayman Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184449

This paper introduces two novel approaches to estimate the clique potentials in binary and multilevel realizations of Gibbs Markov random field (GMRF) models. The first approach employs a genetic algorithm (CA) in order to arrive at the closest synthesized image that resembles the original "observed" image. The Second approach is used to estimate the parameters of Gaussian Markov random field. Given an image formed of a number of classes, an initial class density is assumed and the parameters of the densities are estimated using the EM approach. Convergence to the true distribution is tested using the Levy distance. The segmentation of classes is performed iteratively using the ICM algorithm and a genetic algorithm (GA) search approach that provides the maximum a posteriori probability of pixel classification. During the iterations, the GA approach is used to select the clique potentials of the Gibbs-Markov models used for the observed image. The algorithm stops when a fitness function, equivalent to the maximum a posteriori probability, does not change. The approach has been tested on synthetic and real images and is shown to provide satisfactory results. © Commonwealth of Australia 2003.

关键词： Genetic algorithms

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Two Sequential Stages Classifier for Multispectral Data

Two Sequential Stages Classifier for Multispectral Data

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Conference on Computer vision and Pattern Recognition Workshop, CVPRW 2003

作者： Mohamed, Refaat M. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville LouisvilleKY40292 United States

ISBN: (纸本)0769519008

In this paper, we present an approach for the classification of remote sensing multispectral data, which consists of two sequential stages. The first stage exploits the capabilities of the Support Vector Machines (SVM) approach for density estimation and uses it in a Bayes classification setup. In a typical image, the class of a pixel is highly dependent on the classes of its neighbor pixels. The second stage exploits the dependency of the classes. We incorporate this dependency using stochastic modeling of the context as a Markov Random Field (MRF). The MRF is modeled using Besag model and implemented using the Iterative Conditional Modes (ICM) algorithm. Results show that the stochastic modeling approach enhances the results and provides reasonable smoothness in the classified image. © 2003 IEEE.

关键词： Remote sensing

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Extraction of the superficial facial vasculature, vital signs waveforms and rates using thermal imaging

Extraction of the superficial facial vasculature, vital sign...

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2010 IEEE Computer Society Conference on Computer vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Gault, Travis R. Blumenthal, Nicholas Farag, Aly A. Starr, Tom Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)9781424470297

This work deals with non-invasive and non-intrusive measurements of the human facial vasculature from thermal imaging, and estimates the waveforms and rates of the arterial pulse. The paper addresses the issues involved with use of Long-Wave IR imaging in studies of human biometrics, and focuses on measurements of human's heart rate based on a small number of thermal video frames. Infrared videos of 30 subjects were recorded at two distances. Vascular mapping and multi-resolution analysis are used to calculate a subject's heart rate using only 512 Long-Wave IR video frames (17.07 seconds). This semi-automatic process is typically 89-99% accurate, with average accuracies at both distances at approximately 93%. The work is a step in a comprehensive computer vision system for computational studies on humanmachine interface. © 2010 IEEE.

关键词： Infrared imaging

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An age estimation method to panoramic radiographs from Indonesian individuals

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Telkomnika 2013年第1期11卷 199-206页

作者： Yuniarti, Anny Arifin, Agus Zainal Wijaya, Arya Yudhi Khotimah, Wijayanti Nurul Laboratory of Vision Image Processing and Graphics Department of Informatics Faculty of Information Technology Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia

Dental features can be considered as the best candidate feature for post-mortem identification. If ante-mortem data is unavailable, then forensic experts are needed for reducing the search space by creating post-mortem dental profiling. Age is one of important factors in dental profiling. Manual inspection of dental radiographs suffers from two drawbaks, i.e., intraobserver error and interobserver error. This paper proposed a semi-automatic system for age estimation. There are two phases in developing the proposed system, i.e., the modeling phase and the estimation phase. The modeling phase is the stage for deriving an estimation formula based on known data. In this paper, we use data taken from Javanese people. The estimation phase include the process of defining a Region of Interest (ROI), automatic length computation, and age estimation based on the derived modeling formula. Our experiments showed a promising result, i.e., an average absolute error of 5.2 years, compared to application of the Kvaal method to panoramic radiographs from Turkish individuals that yields a difference of more than 12 years.

关键词： Errors

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A general-purpose platform for 3-D reconstruction from sequence of images

A general-purpose platform for 3-D reconstruction from seque...

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5th International Conference on Information Fusion, FUSION 2002

作者： Eid, Ahmed H. Rashad, Sherif S. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184414

A number of approaches have been proposed in the literature for reconstruction of 3-D objects from sequence of images. Yet, very few studies have been reported on the quantification/validation of the accuracy of these reconstructions. In addition, no design has been reported for a generic vision platform that can allow various modality imaging. The purpose of this paper is two folds: 1) propose a vision platform that lend itself for acquisition of calibrated sequence of images, and concurrently obtain a direct 3-D reconstruction by laser scanning;and 2) develop and implement different approaches for 3-D reconstructions from sequence of images. 3-D reconstructions will be evaluated against the 3-D scanning generated from a laser scanner. Validation of the reconstructions is made by pairwise comparison with the 3-D scanning results. Preliminary studies with the proposed vision platform show a good promise for its use in the validation of various 3-D reconstructions, registration and data fusion. © 2002 Int. Soc. of Information Fusion.

关键词： Scanning

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Experiments in multimodality image classification and data fusion

Experiments in multimodality image classification and data f...

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5th International Conference on Information Fusion, FUSION 2002

作者： Farag, Aly A. Mohanied, Refaat M. Mahdi, Hani Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184414

In this paper, we report the results of some experiments on image classification and data fusion of remote sensing images, as part of ongoing efforts at the CVIP to develop a general strategy for the analysis of multimodality imaging. Statistical and Fuzzy logic approaches have been employed in these experiments. In all, six different algorithms for image classification, and an image fusion algorithm have been implemented and evaluated on common data sets. These algorithms are: (1) Supervised Parametric Bayes Classifier;(2) Non-parametric Bayesian Classifier using the Parzen density estimate;(3) Maximum a posteriori classification using the k-nearest neighbors (k-NN) approach;(4) MAP Estimation using Markov random field modeling;(5) a Fuzzy logic approach;and (6) a novel discriminate function classifier. The AMP segmentation of the regions in the image has been implemented using the Iterated Conditional Mode (ICM) optimization method. This approach provided the best results, in terms of the minimum probability of error and best reliability. A novel decision fusion algorithm, based on the a priori class conditional probability, has been applied to the classifiers' output. © 2002 Int. Soc. of Information Fusion.

关键词： Fuzzy logic

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A new unsupervised approach for the classification of multispectral data

A new unsupervised approach for the classification of multis...

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6th International Conference on Information Fusion, FUSION 2003

作者： Mohamed, Refaat M. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184449

In this paper, we present a new approach for unsupervised pixel-wise classification of multispectral data. In this approach, we estimate the number of classes in a data set as well as the parameters of each class. This approach doesn't require training samples. A scene is modeled as a realization of a random field formed of a mixture distribution. We employ an EM algorithm to estimate the parameters of this mixture. The algorithm iterates to estimate the proper number of classes that compose the scene, and also the parameters of these classes. Theoretically, the algorithm can be applied for arbitrary forms of distributions for the classes in the scene, either parametric or non parametric. This paper focuses on the parametric estimation case. The approach has been applied to synthetic and real world multispectral data and provided quite encouraging results compared to other classical classification approaches. © Commonwealth of Australia 2003.

关键词： Classification (of information)

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