Human Identification Using Automatic and Semi‐Automatically Detected Facial Marks

Continuing advancements in the field of digital cameras and surveillance imaging devices have led law enforcement and intelligence agencies to use analysis of images and videos for the investigation and prosecution of crime. When determining identity from photographic evidence, forensic analysts perform comparison of visible facial features manually, which is inefficient. In this study, we will address research efforts to use facial marks as biometric signatures to distinguish between individuals. We propose two systems to assist forensic analysts during photographic comparison: an improved multiscale facial mark system in which facial marks are detected automatically, and a semi‐automatic facial mark system that integrates human knowledge within the improved multiscale facial mark system. Experiment results employ a high‐resolution time‐elapsed dataset acquired at the University of Notre Dame between 2009 and 2011. The results indicate that the geometric distributions of facial mark patterns can be used to distinguish between individuals.     

3D forensic facial approximation: Implementation protocol in a forensic activity

The primary objective of this paper is to report on the successful implementation of forensic facial approximation in a real case in the forensic context. A three‐dimensional (3D) facial approximation protocol of the skull was performed with free software, applying techniques in a virtual environment that have already been consolidated in the literature. The skull was scanned with the photogrammetry technique, the digital replica was imported in the Blender software (Blender Foundation, Amsterdam) and individualized model sketches of the face were traced with the MakeHuman software (MakeHuman Org) according to the anthropological profile of the victim. The face created was imported in Blender, where it was adapted, modeled, and sculpted on the 3D skull and its soft tissue markers, using an American open‐source application of the technique in the digital environment. The face created in a virtual environment was recognized and legal identification procedures were started, resulting in the more agile delivery of the disappeared body to its next of kin. It is therefore concluded that facial approximation may not be a primary method of human identification, but it can be satisfactorily applied in the forensic field as an individual recognition resource. It has great value in narrowing the search, reducing the number of alleged victims, and leading to identification tests, therefore significantly reducing the number of genetic DNA (deoxyribonucleic acid) tests—which are considered costly for the State or Federation—and consequently reducing the waiting time before delivery of the body to its family.     

应用数字图像识别系统研究正畸治疗前后腭皱形态变化

目的利用腭皱数字图像识别系统对正畸治疗前后腭皱形态匹配正确率的分析研究,为法医学中同一认定提供理论依据。方法利用正畸患者治疗前后腭皱形态数字图像,通过腭皱数字图像识别系统对图像的特征进行提取并收录到腭皱数字库,运用Matlab软件完成对腭皱形态数字图像的信息匹配处理。结果正畸治疗前后,个体性检测匹配正确率各自都达到100%。正畸治疗前后腭皱形态匹配正确率为95.67%,配对检验结果 P0.05,具有统计学意义。结论腭皱形态具有高度的个体特异性,正畸治疗后腭皱形态会发生多种变化,但对同一认定的影响不大。腭皱形态识别为法医学同一认定提供一种新的方法和途径。     

Image conditions for machine-based face recognition of juvenile faces

Machine-based facial recognition could help law enforcement and other organisations to match juvenile faces more efficiently. It is especially important when dealing with indecent images of children to minimise the workload, and deal with moral and stamina challenges related to human recognition. With growth related changes, juvenile face recognition is challenging. The challenge not only relates to the growth of the child’s face, but also to face recognition in the wild with unconstrained images. The aim of the study was to evaluate how different conditions (i.e. black and white, cropped, blur and resolution reduction) can affect machine-based facial recognition of juvenile age progression. The study used three off-the-shelf facial recognition algorithms (Microsoft Face API, Amazon Rekognition, and Face++) and compared the original images and the age progression images under the four image conditions against an older image of the child. The results showed a decrease in facial similarity with an increased age gap, in comparison to Microsoft; Amazon and Face++ showed higher confidence scores and are more resilient to a change in image condition. The image condition ‘black and white’ and ‘cropped’ had a negative effect across all three APIs. The relationship between age progression images and the younger original image was explored. The results suggest manual age progression images are no more useful than the original image for facial identification of missing children, and Amazon and Face++ performed better with the original image.     

图像降噪和增强对人脸识别系统识别性能的影响

目的研究图像降噪和图像增强方法对人脸识别系统识别性能的影响,以期为人脸识别系统应用过程中的图像处理方法选取提供理论指导和技术方案。方法收集33起人像鉴定领域实际案例中的人脸图像素材,研究以高斯滤波和小波变换为代表的图像降噪技术以及具有边缘保持和小波变换特性的单帧图像超分辨率增强技术对人脸识别系统识别性能的影响,并对不同图像处理方法对人脸识别性能的影响进行量化比较分析。结果本文研究的图像降噪技术均显著提高了人脸识别系统的识别准确性,而图像增强技术虽然提高了人脸图像显示效果,但对人脸识别系统的识别性能无正向促进作用。此外,高斯模糊图像处理的图像降噪方法虽然简单,但与本文研究的其他方法比较,其在人脸识别系统识别性能改善方面效果最显著。结论人脸图像质量对人脸识别系统的识别性能具有显著影响,可以通过图像处理技术改善人脸图像质量进而提高人脸识别系统的识别准确性。其中,图像降噪处理可以显著提高人脸识别系统的识别性能,且比图像增强技术更适合于实际人像鉴定应用中的人脸识别系统识别性能增强。     

The mask detection technology for occluded face analysis in the surveillance system

The surveillance systems have been widely used in automatic teller machines (ATMs), banks, convenient stores, etc. For example, when a customer uses the ATM, the surveillance systems will record his/her face information. The information will help us understand and trace who withdrew money. However, when criminals use the ATM to withdraw illegal money, they usually block their faces with something (in Taiwan, criminals usually use safety helmets or masks to block their faces). That will degrade the purpose of the surveillance system. In previous work, we already proposed a technology for safety helmet detection. In this paper, we propose a mask detection technology based upon automatic face recognition methods. We use the Gabor filters to generate facial features and utilize geometric analysis algorithms for mask detection. The technology can give an early warning to save-guards when any "customer" or "intruder" blocks his/her face information with a mask. Besides, the technology can assist face detection in the automatic face recognition system. Experimental results show the performance and reliability of the proposed technology.     

深度学习在图像识别及骨龄评估中的优势及应用前景

深度学习以及神经网络模型是近年来机器学习及人工智能领域新的研究方向及热点问题。深度学习在图像识别、语音识别应用中已取得了突破性进展,在人脸识别、信息检索等领域也展示出独特优势,得到了广泛应用。骨骼X线图像显示黑白灰不同阶度的变化,具有黑白对比、层次差异的图像特征,基于深度学习在图像识别中的优势,我们将其与骨龄评估研究有机结合,旨在为构建法医学骨龄自动化评估系统提供基础性数据。本文综述了深度学习的基本概念及其网络结构,阐述了近年来深度学习在国内外不同研究领域图像识别中的研究进展,以及深度学习在骨龄评估中的优势及应用前景。     

Tests of one Brazilian facial reconstruction method using three soft tissue depth sets and familiar assessors

Facial reconstruction is a method that seeks to recreate a person's facial appearance from his/her skull. This technique can be the last resource used in a forensic investigation, when identification techniques such as DNA analysis, dental records, fingerprints and radiographic comparison cannot be used to identify a body or skeletal remains. To perform facial reconstruction, the data of facial soft tissue thickness are necessary. Scientific literature has described differences in the thickness of facial soft tissue between ethnic groups. There are different databases of soft tissue thickness published in the scientific literature. There are no literature records of facial reconstruction works carried out with data of soft tissues obtained from samples of Brazilian subjects. There are also no reports of digital forensic facial reconstruction performed in Brazil. There are two databases of soft tissue thickness published for the Brazilian population: one obtained from measurements performed in fresh cadavers (fresh cadavers' pattern), and another from measurements using magnetic resonance imaging (Magnetic Resonance pattern). This study aims to perform three different characterized digital forensic facial reconstructions (with hair, eyelashes and eyebrows) of a Brazilian subject (based on an international pattern and two Brazilian patterns for soft facial tissue thickness), and evaluate the digital forensic facial reconstructions comparing them to photos of the individual and other nine subjects. The DICOM data of the Computed Tomography (CT) donated by a volunteer were converted into stereolitography (STL) files and used for the creation of the digital facial reconstructions. Once the three reconstructions were performed, they were compared to photographs of the subject who had the face reconstructed and nine other subjects. Thirty examiners participated in this recognition process. The target subject was recognized by 26.67% of the examiners in the reconstruction performed with the Brazilian Magnetic Resonance Pattern, 23.33% in the reconstruction performed with the Brazilian Fresh Cadavers Pattern and 20.00% in the reconstruction performed with the International Pattern, in which the target-subject was the most recognized subject in the first two patterns. The rate of correct recognitions of the target subject indicate that the digital forensic facial reconstruction, conducted with parameters used in this study, may be a useful tool.     

A new retrieval system for a database of 3D facial images

A new retrieval system for a 3D facial image database was designed and its reliability was experimentally examined. This system has two steps, firstly to automatically adjust the orientation of all 3D facial images in a database to that of the 2D facial image of a target person, and then to identify the facial image of the target person from the adjusted 3D facial images in the database using a graph-matching method. From the experimental study [M. Yoshino, K. Imaizumi, T. Tanijiri, J.G. Clement, Automatic adjustment of facial orientation in 3D face image database, Jpn. J. Sci. Tech. Iden. 8 (2003) 41-47], it is concluded that the software developed for the first step will be applicable to the automatic adjustment of facial orientation in the 3D facial image database. In 28 out of 110 sets (25.5%), the 3D image of the target person was chosen as the best match (from a database of 132 3D facial images) according to the similarity of the facial image characteristics based on the graph matching. The 3D facial image of the target person was ranked in the top of 10 of the database in 75 out of 110 sets (68.2%). These results suggest that this system is inadequate for the identification level, but may be feasible for screening method in a small database. It will be necessary to further pursue the possibility of realization of a facial image retrieval system for a large database such as suspects' facial images in future.     

Using JPEG quantization tables to identify imagery processed by software

The quantization tables used for JPEG compression can also be used to help separate images that have been processed by software from those that have not. This loose classification is sufficient to greatly reduce the number of images an examiner must consider during an investigation. As illicit imagery prosecutions depend on the authenticity of the images involved, this capability is an advantage for forensic examiners. This paper explains how quantization tables work, how they can be used for image source identification, and the implications for computer forensics.     

Passive forensics in image and video using noise features: A review

Due to present of enormous free image and video editing software on the Internet, tampering of digital images and videos have become very easy. Validating the integrity of images or videos and detecting any attempt of forgery without use of active forensic technique such as Digital Signature or Digital Watermark is a big challenge to researchers. Passive forensic techniques, unlike active techniques, do not need any preembeded information about the image or video. The proposed paper presents a comprehensive review of the recent developments in the field of digital image and video forensic using noise features. The previously existing methods of image and video forensics proved the importance of noises and encourage us for the study and perform extensive research in this field. Moreover, in this paper, forensic task cover mainly source identification and forgery detection in the image and video using noise features. Thus, various source identification and forgery detection methods using noise features are reviewed and compared in this paper for image and video. The overall objective of this paper is to give researchers a broad perspective on various aspects of image and video forensics using noise features. Conclusion part of this paper discusses about the importance of noise features and the challenges encountered by different image and video forensic method using noise features.     

Combination of Face Regions in Forensic Scenarios

This article presents an experimental analysis of the combination of different regions of the human face on various forensic scenarios to generate scientific knowledge useful for the forensic experts. Three scenarios of interest at different distances are considered comparing mugshot and CCTV face images using MORPH and SC face databases. One of the main findings is that inner facial regions combine better in mugshot and close CCTV scenarios and outer facial regions combine better in far CCTV scenarios. This means, that depending of the acquisition distance, the discriminative power of the facial regions change, having in some cases better performance than the full face. This effect can be exploited by considering the fusion of facial regions which results in a very significant improvement of the discriminative performance compared to just using the full face.     

Data fragment forensics for embedded DVR systems

A recent increase in the prevalence of embedded systems has led them to become a primary target of digital forensic investigations. Embedded systems with DVR (Digital Video Recorder) capabilities are able to generate multimedia (video/audio) data, and can act as vital pieces of evidence in the field of digital forensics.To counter anti-forensics, it is necessary to derive systematic forensic techniques that can be used on data fragments in unused (unallocated) areas of files or images. Specifically, the techniques should extract meaningful information from various types of data fragments, such as non-sequential fragmentation and missing fragments overwritten by other data.This paper proposes a new digital forensic system for use on video data fragments related to DVRs. We demonstrate in detail special techniques for the classification, reassembly, and extraction of video data fragments, and introduce an integrated framework for data fragment forensics based on techniques described in this paper.     

The Effect of Image Quality and Forensic Expertise in Facial Image Comparisons

Images of perpetrators in surveillance video footage are often used as evidence in court. In this study, identification accuracy was compared for forensic experts and untrained persons in facial image comparisons as well as the impact of image quality. Participants viewed thirty image pairs and were asked to rate the level of support garnered from their observations for concluding whether or not the two images showed the same person. Forensic experts reached their conclusions with significantly fewer errors than did untrained participants. They were also better than novices at determining when two high‐quality images depicted the same person. Notably, lower image quality led to more careful conclusions by experts, but not for untrained participants. In summary, the untrained participants had more false negatives and false positives than experts, which in the latter case could lead to a higher risk of an innocent person being convicted for an untrained witness.     

Digital photography as an object of forensic medical examination

The possibility of diagnosing skin lesions by means of digital pictures was investigated. A "Zenit ET" film camera, HP flatbed scanner, amateur "'Panasonic" and "Sony" videocameras, miniature USB camera and digital photocameras were used to obtain images. Above 1000 images were studied. Criteria were fixed for the required quality of images. A method was developed to formalize images by means of a color etalon and mathematical assessment of formalized skin lesions. Stages were suggested for the computer-based analysis of images. Computer software was developed for the automated formalization of images and for the statistical processing of values of image elements. It was demonstrated that digital photography can be an independent informative object of forensic medical examination.     

辽宁汉族青年女性面部不对称性的分析

目的研究辽宁汉族青年女性面部的不对称性,为面部识别和颅面复原提供数据。方法随机选择100例正常青年女性,采用MRI摄片,应用VG Studio 2.2MAX软件测量面部的标志点,测量后的右、左侧面部坐标进行欧几里德几何距离矩阵分析（EDMA）,最后使用Geomagic Wrap 12软件对左侧面部三维图像进行镜像合成,生成完全对称的镜像面部并与真实面部进行比较。结果 EDMA分析显示,右、左侧面部有显著形态学差异,bootstrap检验T=1.402,P=0.001,形状差异矩阵（FDM）比值（右侧比左侧）在0.95-1.05的有224个占85%,FDM比值小于0.95和大于1.05的部分有40个占15%,40个不对称比值中有15个小于0.95占37.5%,25个比值大于1.05占62.5%。Geomagic Wrap 12分析结果显示镜像合成的面部与真实面部图像有明显差异。结论辽宁汉族青年女性面部不对称,不对称性为15%,右侧面部比左侧面部不对称性影响大。     

Digital imaging methods as an aid in dental identification of human remains

The physical comparison of known (K) and questioned (Q) evidence samples is an accepted tool in numerous forensic identification disciplines (1). A subset of this process is the use of antemortem and postmortem dental radiographs to identify unidentified human remains. This method has been generally accepted for decades (2). The outcome is performed with a considerable degree of accuracy, due in part to a finite pool of possible candidates for identification derived via the NCIC database, passenger lists, and law enforcement Missing Persons reports. This paper describes a dental identification comparison protocol that incorporated digital imaging technology in this process. The computer was used to create digital exemplars of the K and Q evidence that were spatially and quantitatively compared (3). The digital mode allowed direct metric and morphologic comparison through the aid of a digital camera, desktop computer, monitor, and printer. The well-known computer program Adobe Photoshop 5.0 (4) was used to process the digital information in two forensic cases described in this paper. It is a commercially available digital imaging editing program that is operated on laptop and desktop computers possessing sufficient chip speed and RAM (Pentium II or equivalent and at least 76MB RAM) to open the large-size files generated by high-resolution digital capture devices. This program accepts raster-based image formats (e.g. .JPG, .BMP). Photoshop is noted for its diverse imaging functions, which allow the computer monitor to be used as a comparison microscope when Q and K sample images are tiled side-by-side and/or superimposed. Two and three-dimensional Q and K evidence samples can be individually digitized and then independently resized to allow two-dimensional comparison. The investigator also has the ability to create magnified images (200% to 300%) when the original digital image has been captured at near photoquality resolution (300 dpi). The visual comparison of physical features on the computer monitor permits a large field of view and robust digital control over image quality. Photographic measurement and enhancement features of Adobe Photoshop mimics and in some circumstances surpasses the historic use of conventional photographic manipulation in forensic casework. This paper presents two cases processed via routine forensic odontology identification protocols. These protocols had minimal results due to limitations described in the case histories. The additional application of digital methods proved useful in the ultimate identification of these human remains.     

IoT forensics: Exploiting unexplored log records from the HIKVISION file system

CCTV surveillance systems are IoT products that can be found almost everywhere. Their digital forensic analysis often plays a key role in solving crimes. However, it is common for these devices to use proprietary file systems, which frequently hinders a complete examination. HIKVISION is a well-known manufacturer of such devices that typically ships its products with its proprietary file system. The HIKVISION file system has been analyzed before but that research has focused on the recovery of video footage. In this paper, the HIKVISION file system is being revisited regarding the log records it stores. More specifically, these log records are thoroughly examined to uncover both their structure and meaning. These unexplored pieces of evidence remain unexploited by major commercial forensic software, yet they can contain critical information for an investigation. To further assist digital forensic examiners with their analysis, a Python utility, namely the Hikvision Log Analyzer, was developed as part of this study that can automate part of the process.     

A new experimental approach to computer-aided face/skull identification in forensic anthropology

The present study introduces a new approach to computer-assisted face/skull matching used for personal identification purposes in forensic anthropology.In this experiment, the authors formulated an algorithm able to identify the face of a person suspected to have disappeared, by comparing the respective person's facial image with the skull radiograph. A total of 14 subjects were selected for the study, from which a facial photograph and skull radiograph were taken and ultimately compiled into a database, saved to the hard drive of a computer. The photographs of the faces and corresponding skull radiographs were then drafted using common photographic software, taking caution not to alter the informational content of the images. Once computer generated, the facial images and menu were displayed on a color monitor. In the first phase, a few anatomic points of each photograph were selected and marked with a cross to facilitate and more accurately match the face with its corresponding skull. In the second phase, the above mentioned cross grid was superimposed on the radiographic image of the skull and brought to scale. In the third phase, the crosses were transferred to the cranial points of the radiograph. In the fourth phase, the algorithm calculated the distance of each transferred cross and the corresponding average. The smaller the mean value, the greater the index of similarity between the face and skull.A total of 196 cross-comparisons were conducted, with positive identification resulting in each case. Hence, the algorithm matched a facial photograph to the correct skull in 100% of the cases.     

“I couldn't find it your honour,it mustn't be there!” – Tool errors,tool limitations and user error in digital forensics

The field of digital forensics maintains significant reliance on the software it uses to acquire and investigate forms of digital evidence. Without these tools, analysis of digital devices would often not be possible. Despite such levels of reliance, techniques for validating digital forensic software are sparse and research is limited in both volume and depth. As practitioners pursue the goal of producing robust evidence, they face the onerous task of both ensuring the accuracy of their tools and, their effective use. Whilst tool errors provide one issue, establishing a tool's limitations also provides an investigatory challenge leading the potential for practitioner user-error and ultimately a grey area of accountability. This article debates the problems surrounding digital forensic tool usage, evidential reliability and validation.