Multi-resolution image fusion technique and its application to forensic science

Image fusion is a process of combining two or more images into an image. It can extract features from source images, and provide more information than one image can. Multi-resolution analysis plays an important role in image processing, it provides a technique to decompose an image and extract information from coarse to fine scales. In some practical forensic examinations (such as the cartridge image check), we cannot obtain all information from just one image; on the contrary, we need information from images with difference light sources (or light ways). In this paper, we apply an image fusion method based on multi-resolution analysis to forensic science. Synthetic and real images (such as images from closed-up photography and flash photography) are used to show the capability of the multi-resolution image fusion technique.     

多源图像融合技术及其在公安刑事摄影工作中的应用

近年来,多源图像融合技术的应用越来越多,它可以将同一场景以不同成像方式或者不同成像时间获得的不同图像融合为一幅图像。这种技术可以综合多张照片的信息量,提高视觉感知,便于进行计算机的处理,因此,可在公安刑事摄影工作中用于对疑难指纹、立体痕迹、强反光客体痕迹、高逆光现场照片等的拍摄和处理,从而最大程度的准确反映被摄景物的实际情况。     

Photographic Image Comparison of Vegetation

Images and videos are common types of evidence in crime scene investigations and laboratory analysis. Images may be taken by the suspect and/or by crime scene investigators and may serve as crucial elements in forensic laboratory analysis. Forensic photographic image comparison is the process of comparing one or more objects or persons in photographs/images when at least one image is known to be related to a crime. The forensic examiner usually compares the images in order to determine whether or not an association between the exhibits in the images can be made. This paper proposes an extension to the currently prevalent photographic image examination method. The extension introduces comparison of landscape and vegetation over time. It is revealed that similarities between images may still be found between the period of time the suspect photograph was taken and the period the crime scene investigator took the photograph from the same area. In this case report, two suspects to be involved in growing a marijuana field were arrested by the police. The forensic experts were asked to examine images taken by the crime scene investigators and to compare them to the images found in the suspects’ phones. They then tried to determine whether the suspects could be linked to the specific locations. While applying techniques derived from morphological comparison methodologies, the plants at the scene provided significant additional information. A tree trunk, branches, and twigs on a hedge in the photographs revealed specific individual characteristics that led the examiner to reach a conclusive decision.     

The Use of Near‐Infrared Photography to Image Fired Bullets and Cartridge Cases

An imaging technique that is capable of reducing glare, reflection, and shadows can greatly assist the process of toolmarks comparison. In this work, a camera with near‐infrared (near‐IR) photographic capabilities was fitted with an IR filter, mounted to a stereomicroscope, and used to capture images of toolmarks on fired bullets and cartridge cases. Fluorescent, white light‐emitting diode (LED), and halogen light sources were compared for use with the camera. Test‐fired bullets and cartridge cases from different makes and models of firearms were photographed under either near‐IR or visible light. With visual comparisons, near‐IR images and visible light images were comparable. The use of near‐IR photography did not reveal more details and could not effectively eliminate reflections and glare associated with visible light photography. Near‐IR photography showed little advantages in manual examination of fired evidence when it was compared with visible light (regular) photography.     

Color Separation in Forensic Image Processing Using Interactive Differential Evolution

Color separation is an image processing technique that has often been used in forensic applications to differentiate among variant colors and to remove unwanted image interference. This process can reveal important information such as covered text or fingerprints in forensic investigation procedures. However, several limitations prevent users from selecting the appropriate parameters pertaining to the desired and undesired colors. This study proposes the hybridization of an interactive differential evolution (IDE) and a color separation technique that no longer requires users to guess required control parameters. The IDE algorithm optimizes these parameters in an interactive manner by utilizing human visual judgment to uncover desired objects. A comprehensive experimental verification has been conducted on various sample test images, including heavily obscured texts, texts with subtle color variations, and fingerprint smudges. The advantage of IDE is apparent as it effectively optimizes the color separation parameters at a level indiscernible to the naked eyes.     

A study on the false positive rate of Stegdetect

In this paper we analyse Stegdetect, one of the well-known image steganalysis tools, to study its false positive rate. In doing so, we process more than 40,000 images randomly downloaded from the Internet using Google images, together with 25,000 images from the ASIRRA (Animal Species Image Recognition for Restricting Access) public corpus. The aim of this study is to help digital forensic analysts, aiming to study a large number of image files during an investigation, to better understand the capabilities and the limitations of steganalysis tools like Stegdetect. The results obtained show that the rate of false positives generated by Stegdetect depends highly on the chosen sensitivity value, and it is generally quite high. This should support the forensic expert to have better interpretation in their results, and taking the false positive rates into consideration. Additionally, we have provided a detailed statistical analysis for the obtained results to study the difference in detection between selected groups, close groups and different groups of images. This method can be applied to any steganalysis tool, which gives the analyst a better understanding of the detection results, especially when he has no prior information about the false positive rate of the tool.     

光谱成像检验技术

光谱成像组合了光谱技术和成像技术。通过运用成像光谱仪 ,光谱成像方法可以记录被检验物体在一个较宽光谱范围内均匀密集分布的窄波段反射光或荧光亮度分布影像 ,形成含有物体亮度信息和光谱信息的光谱影像集。这种技术方法可以用于物证的形态特征检验和物质成分检验。相对传统光谱检验或成像检验技术 ,光谱成像检验的能力和效果都具有明显优势。     

Pistol image retrieval by shape representation

Databases have been used to record data in forensic science, such as fingerprints, shoeprints, and photos. In traditional databases, we use “text” as the “keyword” for retrieving data (text-keyword retrieval); however, in some applications, “text” is not proper to describe the searching target, and in this case, “image” plays an important role. In this paper, we use “image features” as the “keywords”, and show its potential for building up a prototype of pistol image databases.In current firearm databases of forensic science, the retrieval method is still by text-keyword retrieval. For experienced forensic examiners, this kind of databases may satisfy their requirement. However, for people who have little gun knowledge, how can they find the possible gun candidates or similar guns in the databases, if there are not any available words or marks on the gun? In this paper, we try to retrieve similar pistol images by the pistol shape instead of “text-keyword”. This method can narrow down the searching range while identifying pistols by firearm databases.There are more than 300 pistol images in our pistol image database. From the experimental results, we can retrieve the similar pistol images in top five candidates for each pistol image.     

The evidential value of distorted and rectified digital images in footwear imprint examination

The procedure for forensic photography requires that the film plane be parallel to the taken image. Another procedure must be used when the print is located on reflecting surfaces such as vehicles, or faint marks on porous surfaces. Examination was made of the evidential value of footprint images received from the scene or taken deliberately at an angle out of proper perspective (i.e., the lens axis is not perpendicular to the target plane). An artificial target was prepared and photographed from several lens axis angles ranging from 10 degrees to 85 degrees to the perpendicular, and then rectified using the Adobe Photoshop Version 7.0. It was found that at angles less than 40 degrees , the shape and location of all the individual characteristics were similar enough in comparison to the original image. In images taken at higher angles, the original image could not be adequately restored. The full potential of this image, therefore, could not be achieved after rectification. The results of this study show that the images of a footprint taken at an angle less than 40 degrees , preserve the evidential value of the unique characteristics.     

A forensic science perspective on the role of images in crime investigation and reconstruction

This article presents a global vision of images in forensic science. The proliferation of perspectives on the use of images throughout criminal investigations and the increasing demand for research on this topic seem to demand a forensic science-based analysis. In this study, the definitions of and concepts related to material traces are revisited and applied to images, and a structured approach is used to persuade the scientific community to extend and improve the use of images as traces in criminal investigations. Current research efforts focus on technical issues and evidence assessment. This article provides a sound foundation for rationalising and explaining the processes involved in the production of clues from trace images. For example, the mechanisms through which these visual traces become clues of presence or action are described. An extensive literature review of forensic image analysis emphasises the existing guidelines and knowledge available for answering investigative questions (who, what, where, when and how). However, complementary developments are still necessary to demystify many aspects of image analysis in forensic science, including how to review and select images or use them to reconstruct an event or assist intelligence efforts. The hypothetico-deductive reasoning pathway used to discover unknown elements of an event or crime can also help scientists understand the underlying processes involved in their decision making. An analysis of a single image in an investigative or probative context is used to demonstrate the highly informative potential of images as traces and/or clues. Research efforts should be directed toward formalising the extraction and combination of clues from images. An appropriate methodology is key to expanding the use of images in forensic science.     

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.     

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.     

Reflectance Transformation Imaging (RTI) for the Documentation of Saw Mark Characteristics

Photography is widely accepted as a means of forensic case documentation and evaluation. In cases of criminal dismemberment digital microscopy is commonly used to assess marks left on the bone. Reflectance transformation imaging (RTI) is a computational photography technique which documents and enhances the three-dimensional (3D) reflectance properties of the surface of an object. RTI has primarily been used in the cultural heritage sector but has recently transitioned into forensic science. This study examines the use of RTI for the documentation and presentation of cut surface characteristics on fully sectioned long bones. Juvenile pig radii were bisected using three different handsaws, chosen as handsaws are the most common implement used in criminal dismemberments. The resulting 42 cut surfaces were then documented with a digital microscope and RTI. Four rendering modes were applied to the default RTI image, with diffuse gain being the most beneficial to accentuate cut surface features. Although great care must be taken when obtaining the photographic sequences necessary for detailed RTI analysis, RTI is relatively inexpensive, expeditious, and easy to use, and creates highly detailed, virtually interactive images. RTI may not replace microscopic methods of saw mark analysis, however could prove useful for the documentation, image sharing, and presentation of forensic evidence.     

The applicability of holography in forensic identification: a fusion of the traditional optical technique and digital technique

In this study, the applicability of holography in the 3-dimensional recording of forensic objects such as skulls and mandibulae, and the accuracy of the reconstructed 3-D images, were examined. The virtual holographic image, which records the 3-dimensional data of the original object, is visually observed on the other side of the holographic plate, and reproduces the 3-dimensional shape of the object well. Another type of holographic image, the real image, is focused on a frosted glass screen, and cross-sectional images of the object can be observed. When measuring the distances between anatomical reference points using an image-processing software, the average deviations in the holographic images as compared to the actual objects were less than 0.1 mm. Therefore, holography could be useful as a 3-dimensional recording method of forensic objects. Two superimposition systems using holographic images were examined. In the 2D-3D system, the transparent virtual holographic image of an object is directly superimposed onto the digitized photograph of the same object on the LCD monitor. On the other hand, in the video system, the holographic image captured by the CCD camera is superimposed onto the digitized photographic image using a personal computer. We found that the discrepancy between the outlines of the superimposed holographic and photographic dental images using the video system was smaller than that using the 2D-3D system. Holography seemed to perform comparably to the computer graphic system; however, a fusion with the digital technique would expand the utility of holography in superimposition.     

Detection of latent bloodstains beneath painted surfaces using reflected infrared photography

Bloodstain evidence is a highly valued form of physical evidence commonly found at scenes involving violent crimes. However, painting over bloodstains will often conceal this type of evidence. There is limited research in the scientific literature that describes methods of detecting painted-over bloodstains. This project employed a modified digital single-lens reflex camera to investigate the effectiveness of infrared (IR) photography in detecting latent bloodstain evidence beneath a layer or multiple layers of paint. A qualitative evaluation was completed by comparing images taken of a series of samples using both IR and standard (visible light) photography. Further quantitative image analysis was used to verify the findings. Results from this project indicate that bloodstain evidence can be detected beneath up to six layers of paint using reflected IR; however, the results vary depending on the characteristics of the paint. This technique provides crime scene specialists with a new field method to assist in locating, visualizing, and documenting painted-over bloodstain evidence.     

Shoeprint image retrieval and crime scene shoeprint image linking by using convolutional neural network and normalized cross correlation

A shoeprint image retrieval process aims to identify and match images of shoeprints found at crime scenes with shoeprint images from a known reference database. It is a challenging problem in the forensic discipline of footwear analysis because a shoeprint found at the crime scene is often imperfect. Recovered shoeprints may be partial, distorted, left on surfaces that do not mark easily, or perhaps come from shoes that do not transfer marks easily. In this study, we present a shoeprint retrieval method by using a convolutional neural network (CNN) and normalized cross-correlation (NCC). A pre-trained CNN was used to extract features from the pre-processed shoeprint images. We then employed NCC to compute a similarity score based on the extracted image features. We achieved a retrieval accuracy of 82% in our experiments, where a “successful” retrieval means that the ground truth image was returned in the top 1% of returned images. We also extend our shoeprint retrieval method to the problem of linking shoeprints recovered from crime scenes. This new method can provide a linkage between two crime scenes if the two recovered shoeprints originated from the same shoe. This new method achieved a retrieval accuracy of 88.99% in the top 20% of returned images.     

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.     

Development of a methodology for the standardisation and improvement of ‘Smartphone’ photography of patterned bruises and other cutaneous injuries

Human bite-mark analyses can play a prominent role in forensic case investigations, including those involving sexual assault. High-quality photographs routinely secure a link between a bite-mark and an individual's dentition. Access to around the clock forensic photography, however, is often limited, resulting in delay and/or missed opportunities to record valuable evidence. The emergence of Smartphone high-quality photographic technology now provides a previously unimagined opportunity to gather timely forensic photographic evidence. Problems can arise, however, due to the relatively poor quality of the photographs, as a result of many of those taking photographs having received little or no forensic photography training. This study compares unassisted photography with assisted photography, by a specifically developed camera application (App), to provide a standardised method for taking forensic photographs. An App, written in Java, was hosted on the Google Android Operating System, on a Samsung Galaxy SII Smartphone. Twenty-four volunteers participated in a study to photograph a pseudo bite-mark using three methods, (1) unassisted (as a control), (2) assisted by an ABFO No.2 right-angled photographic reference scale and (3) assisted by the App. The App, method (3), was shown to consistently outperform methods (1) and (2), demonstrating greater standardisation and precision (p < 0.001). Analysis of the data showed the extent to which acquiring an accurate photograph depends on the image being orthogonal to the camera. It appears likely that the relatively inaccurate photographs acquired by methods (1) and (2), were as a result of deviation from the plane, orthogonal to the bite-mark. Therefore, the App was successful in ensuring that the camera was both orthogonal and at an appropriate distance, relative to the bite-mark. Thus, the App enhanced the abilities of non-experts to acquire more accurate photographs and created the potential to significantly improve the quality of forensic photographs.     

Advanced carving techniques

Carving is the term most often used to indicate the act of recovering a file from unstructured digital forensic images. The term unstructured indicates that the original digital image does not contain useful filesystem information which may be used to assist in this recovery.Typically, forensic analysts resort to carving techniques as an avenue of last resort due to the difficulty of current techniques. Most current techniques rely on manual inspection of the file to be recovered and manually reconstructing this file using trial and error. Manual processing is typically impractical for modern disk images which might contain hundreds of thousands of files.At the same time the traditional process of recovering deleted files using filesystem information is becoming less practical because most modern filesystems purge critical information for deleted files. As such the need for automated carving techniques is quickly arising even when a filesystem does exist on the forensic image.This paper explores the theory of carving in a formal way. We then proceed to apply this formal analysis to the carving of PDF and ZIP files based on the internal structure inherent within the file formats themselves. Specifically this paper deals with carving from the Digital Forensic Research Work-Shop's (DFRWS) 2007 carving challenge.     

Statistical Evaluation of Alternative Light Sources for Bloodstain Photography

Bloodstain photography is important in forensic applications, especially for bloodstain pattern analysis. This study compares the enhancement effect of bloodstain photography using three different types of light source: fluorescent white light, near‐ultraviolet (UV) light‐emitting diode (LED) light, and 410 nm LED light. Randomized complete block designs were implemented to identify the lighting that would statistically produce the best enhancement results for bloodstains on different types of surfaces. Bloodstain samples were prepared on white cotton, brown carpet, tar road, and wood. These samples were photographed in darkroom conditions using a Canon EOS 50D digital SLR camera, with Canon EFS 60 mm f/2.8 Macro USM lens. Two‐way analysis of variance and Fisher's least significant difference test were used to analyze the contrast of the images. The statistical analysis showed that 410 nm light is the best among the tested lights for enhancing bloodstains on the tested surfaces, where the contrast of bloodstain to background was the highest.