• Imaging Science in Dentistry
• /
• v.46 no.4
• /
• pp.297-297
• /
• 2016

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.12
• /
• pp.2153-2158
• /
• 2016

Multimedia such as image, audio, and video is easy to create and distribute with the advance of IT. Since novice uses them for illegal purposes, multimedia forensics are required to protect contents and block illegal usage. This paper presents a multimedia forensic algorithm for video to identify the device used for acquiring unknown video files. First, the way to calculate a sensor pattern noise using Wiener filter (W-SPN) is presented, which comes from the imperfection of photon detectors against light. Then, the way to identify the device is explained after estimating W-SPNs from the reference device and the unknown video. For the experiment, 30 devices including DSLR, compact camera, smartphone, and camcorder are tested and analyzed quantitatively. Based on the results, the presented algorithm can achieve the 96.0% identification accuracy.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.8
• /
• pp.1-9
• /
• 2019

With the development of imaging information communication technology in modern society, imaging acquisition and mass production technology have developed rapidly. However, crime rates using these technology are increased and forensic studies are conducted to prevent it. Identification techniques for image acquisition devices are studied a lot, but the field is limited to images. In this paper, camera model identification technique for video, not image is proposed. We analyzed video frames using the trained model with images. Through training and analysis by considering the frame characteristics of video, we showed the superiority of the model using the P frame. Then, we presented a video camera model identification system by applying a majority-based decision algorithm. In the experiment using 5 video camera models, we obtained maximum 96.18% accuracy for each frame identification and the proposed video camera model identification system achieved 100% identification rate for each camera model.

• Korean Journal of Biological Psychiatry
• /
• v.22 no.3
• /
• pp.109-112
• /
• 2015

Since the early 2000s, there has been a continued interest in lie detection using functional magnetic resonance imaging (fMRI) in neuroscience and forensic sciences, as well as in newly emerging fields including neuroethics and neurolaw. Related fMRI studies have revealed converging evidence that brain regions including the prefrontal cortex, anterior cingulate cortex, parietal cortex, and anterior insula are associated with deceptive behavior. However, fMRI-based lie detection has thus far not been generally accepted as evidence in court, as methodological shortcomings, generalizability issues, and ethical and legal concerns are yet to be resolved. In the present review, we aim to illustrate these achievements and limitations of fMRI-based lie detection.

• Imaging Science in Dentistry
• /
• v.52 no.1
• /
• pp.83-91
• /
• 2022

Purpose: This study assessed the associations between chronological age, dental maturation (DM), cervical vertebrae maturation (CVM), and hand-wrist maturation (HWM) in individuals aged 9-19 years. In addition, this study aimed to derive practical methods to evaluate the skeletal age using DM, CVM, or HWM for orthodontic, medical, and forensic purposes and to compare which of these 3 developmental parameters is more accurate for estimating the age of individuals in a Turkish population. Materials and Methods: Panoramic, lateral cephalometric, and hand-wrist radiographs of 284 patients aged 9-19 years were used in this study. The DM, CVM, and HWM stages were determined. The Kolmogorov-Smirnov, kappa, Wilcoxon, Kruskal-Wallis, chi-square, and Spearman correlation tests and simple linear regression analysis were used for statistical analysis. The significance level was 0.05. Results: Statistically significant differences were found between chronological age and DM, chronological age and CVM, and chronological age and HWM in both sexes (P<0.05). DM did not show statistically significant differences according to sex (P>0.05), but CVM and HWM were statistically different between males and females (P<0.05). The DM-estimated age yielded more accurate values than the other methods. Conclusion: All correlations between skeletal and dental stages were statistically significant. Our results showed that there was no statistically significant difference between chronological age and DM-estimated age. Therefore, it can be concluded that DM stages have the potential to be used for legal purposes.

• Journal of Korean Dental Science
• /
• v.15 no.1
• /
• pp.31-50
• /
• 2022

Purpose: This study was to investigate the types of imaging modalities, analytical methods for age estimation, and the age of the subjects in research on age estimation using dental radiography through a scoping review, and to investigate the overall trends in age estimation studies. Materials and Methods: A scoping review was designed according to the Arksey and O'Malley guidelines and the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. Three electronic databases were used as search sources (Medline, Embase, and Cochrane Library). Studies were classified according to the three main components of the research question. "What are the imaging modalities, analytical methods, and target age in dental imaging-based age estimation studies?" Result: The final 198 studies were selected by two reviewers. The most common imaging modality used in studies was panoramic radiography (69.7%), and studies using cone-beam computed tomography have increased over time. Analytical methods for age estimation were 62.6% in studies based on tooth development and 26.3% in studies using pulp/tooth ratio. The subject age was 27.8% for children and 27.3% for adults. Studies conducted in all age groups comprised the smallest category (5.2%). Conclusion: Panoramic radiography has been the most used types of imaging modalities for age estimation, and the most common analytical method was analysis of tooth development. Most studies targeted specific ages, and very few involved all age groups. Dental age estimation studies should be carried out with appropriate consideration of the imaging modality that is analyzed, the methods that are used, and the age that is targeted.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.5
• /
• pp.1167-1174
• /
• 2015

As the market share of smartphone exponentially increases in mobile market, a number of manufacturers have developed their own operating system. Firefox OS is an open source operating system for the smartphone and tablet which is being developed by the Mozilla Foundation. This OS is designed using JavaScript and operated based on HTML5. Even though the number of manufacturers which release the Firefox OS smartphone is consistently increasing, However it is difficult to analyze artifacts in a smartphone in terms of investigation since existing researches on Firefox OS focused on imaging velocity according to abstract forensic process and block size. In this paper, we propose how to collect data in Firefox OS while minimizing data loss and forensic analysis framework based on analysis results on system and user data leaving in a smartphone.

• Korean Circulation Journal
• /
• v.53 no.1
• /
• pp.52-54
• /
• 2023

• Imaging Science in Dentistry
• /
• v.43 no.1
• /
• pp.1-6
• /
• 2013

Purpose: This study investigated the possible correlation between the mineralization of the second molars and the chronological age of a sample population of the state of Paraiba, Brazil. Materials and Methods: One thousand eight hundred fifty-four digitized panoramic images using a scanner of a private dental radiology service were obtained in six months. Of these, 457 were selected from patients aged 4.6 to 16 years who met certain criteria. The images were assessed twice by a radiologist with 5 years experience. A minimum interval of 30 days between the evaluations of the same patient was established. To analyze the relationship between chronological age, calcification level proposed by Demirjian et al in 1973, gender, and tooth, a multiple linear regression model was adjusted, taking age as the response variable (p<0.05). Results: The gender and calcification level were significantly correlated with the age of the patients (p<0.05). There was a significant difference between the average age of the patients' upper teeth compared to the lower ones in both genders (p<0.05). The dental development occurred earlier in female individuals than in male ones, and there was no significant difference between the right and left second permanent molars. Conclusion: It was observed that ethnic variables are related to certain parameters of age and sex identification in the Brazilian population, providing important information for forensic evaluations.

• Imaging Science in Dentistry
• /
• v.49 no.1
• /
• pp.19-26
• /
• 2019

Purpose: It has been proposed that using new prediction methods, such as neural networks based on dental data, could improve age estimation. This study aimed to assess the possibility of exploiting neural networks for estimating age by means of the pulp-to-tooth ratio in canines as a non-destructive, non-expensive, and accurate method. In addition, the predictive performance of neural networks was compared with that of a linear regression model. Materials and Methods: Three hundred subjects whose age ranged from 14 to 60 years and were well distributed among various age groups were included in the study. Two statistical software programs, SPSS 21 (IBM Corp., Armonk, NY, USA) and R, were used for statistical analyses. Results: The results indicated that the neural network model generally performed better than the regression model for estimation of age with pulp-to-tooth ratio data. The prediction errors of the developed neural network model were acceptable, with a root mean square error (RMSE) of 4.40 years and a mean absolute error (MAE) of 4.12 years for the unseen dataset. The prediction errors of the regression model were higher than those of the neural network, with an RMSE of 10.26 years and a MAE of 8.17 years for the test dataset. Conclusion: The neural network method showed relatively acceptable performance, with an MAE of 4.12 years. The application of neural networks creates new opportunities to obtain more accurate estimations of age in forensic research.