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Counterfeiting of alcoholic beverages, particularly high-value spirits such as whiskey, presents significant challenges for regulators, manufacturers, and consumers. In this study, we introduce and validate a novel application of headspace extraction (HS) followed by gas chromatography with flame ionization detection (GC-FID) for the quantitative determination of ethanol content in 42 suspected counterfeit brazilian samples of whiskeys. This method, in conjunction with visual inspection of material inconsistencies, offers a combined approach to identify potential cases of fraud. The HS-GC-FID findings revealed that only 19% of the analyzed samples had ethanol content in the limits declared on the label, emphasizing the role of ethanol content as a chemical marker for suspected beverage fraud. [Display omitted] • Headspace extraction followed by gas chromatography to examine seized whiskeys. • Ethanol content determination combined with material inspection of suspected samples. • Ethanol content is an important chemical marker of counterfeiting. [ABSTRACT FROM AUTHOR]

Important questions have arisen about the capacity of traditional questioned document methodology to differentiate between genuine and forged exemplars of an author's handwriting. This paper does not address that dispute. The paper describes the first part of a research project investigating whether imitators (forgers) can reliably differentiate between genuine samples and forgeries. This paper takes a different, cognitive neuroscience approach and investigates the overlooked topic of the mental processing of forgeries by forgers. The paper tried to examine the neural mechanisms of imitators' (forgers') attentive processing of forged and genuine exemplars. The data in this initial phase of the study showed imitators experienced more difficulty evaluating their own forgeries perhaps because the forgeries included both the features they had consciously copied and some of their own handwriting characteristics that they could not completely suppress. A subsequent phase of the study will use self-reporting and eye movement tracking studies, in this phase we shall attempt to identify the specific types of features the imitators relied on in correctly classifying the exhibit as a forgery. We shall then enlist the services of experienced questioned document examiners endeavor to determine whether those characteristics appear in genuine exemplars of the forgers' handwriting. The identification of those categories of features may hold the potential for improving both the detection of forgeries and the identification of the forger. [ABSTRACT FROM AUTHOR]

Taking into consideration that the prior CMF detection methods rely on several fixed threshold values in the filtering process, we propose an efficient CMF detection method with an automatic threshold selection, named as CMF-iteMS. The CMF-iteMS recommends a PatchMatch-based CMF detection method that adapts Fourier-Mellin Transform (FMT) as the feature extraction technique while a new automatic threshold selection based on iterative means of regions size (iteMS) procedure is introduced to have flexibility in changing the threshold value for various characteristics (quality, sizes, and attacks) in each input image. To ensure the reliability of the proposed CMF-iteMS, the method is compared with four state-of-the-art CMF detection methods based on Scale Invariant Feature Transform (SIFT), patch matching, multi-scale analysis and symmetry techniques using three available datasets that cover the variety of characteristics in CMF images. The results show that the F-score of the CMF-iteMS outperformed existing CMF detection methods by exceeding an average of 90% F-score values for image-level evaluation and 82% of F-score value for pixel-level evaluation for all datasets in original size. As special attention is given to the image resizing attack, the method is able to maintain the highest performance even if the images in the datasets are resized to 0.25 parameter. [ABSTRACT FROM AUTHOR]

Maliciously edited images, also referred to as tampered or forged images, have become ubiquitous and challenging in recent times with the advent of social media platforms. Image splicing is a kind of image tampering where regions of images are copied and pasted into another image. Image tampering detection is a method for the authenticity verification of images produced as evidence in the court of law and forms a sub problem in image forensics. The aim of our work is to detect and locate the boundaries of image splicing, without a-priori knowledge of the reference image. We propose two methods, of which the first uses classification of texture patterns along with the standard deviations of block discrete cosine transformation of textures. In the second method, we combine the first with image quality artifacts incurred due to image tampering along with the entropy of histograms to get an integrated method. We use a support vector machine classifier for training and testing these approaches. Our methods are tested on two publicly available tamper detection datasets and the results are compared with seven other existing works. It is observed that our integrated method gives best results. We have also tested the proposed methods on a social media dataset and the results are encouraging. [ABSTRACT FROM AUTHOR]

Splicing is one of the most common tampering techniques for image manipulation in many forensic cases. Normally color shift in images due to color temperature of illumination can be seen as intrinsic features relative to imaging process. In splicing forgeries, copied area and pasted target image come from different imaging process, and are likely to have different color shift. In this paper, a novel automated authentication method is presented to expose splicing manipulation and locate manipulated areas by discriminating the inconsistencies of color shift in an image. In order to minimize human interaction on detection of splicing forgeries as well as localization of manipulated areas, a forensic image is divided into blocks with grid-based strategy. After calculation on color temperature of each blocks with white-point algorithm, reference color temperature is obtained with a random restricted algorithm. Then color temperature distance between each block and reference area is calculated sequentially. At last, by comparing color temperature distance with an optimized threshold determined by OSTU algorithm. This method enables us to judge if splicing has occurred and furthermore localize manipulated area simultaneously. Experiments show that the proposed method can speed up the quantitative detection of possible splicing manipulation and localize manipulated area automatically. [ABSTRACT FROM AUTHOR]

Videos are acceptable as evidence in the court of law, provided its authenticity and integrity are scientifically validated. Videos recorded by surveillance systems are susceptible to malicious alterations of visual content by perpetrators locally or remotely. Such malicious alterations of video contents (called video forgeries) are categorized into inter-frame and intra-frame forgeries. In this paper, we propose inter-frame forgery detection techniques using tamper traces from spatio-temporal and compressed domains. Pristine videos containing frames that are recorded during sudden camera zooming event, may get wrongly classified as tampered videos leading to an increase in false positives. To address this issue, we propose a method for zooming detection and it is incorporated in video tampering detection. Frame shuffling detection, which was not explored so far is also addressed in our work. Our method is capable of differentiating various inter-frame tamper events and its localization in the temporal domain. The proposed system is tested on 23,586 videos of which 2346 are pristine and rest of them are candidates of inter-frame forged videos. Experimental results show that we have successfully detected frame shuffling with encouraging accuracy rates. We have achieved improved accuracy on forgery detection in frame insertion, frame deletion and frame duplication. [ABSTRACT FROM AUTHOR]

The so-called copy-move forgery, based on copying an object and pasting in another location of the same image, is a common way to manipulate image content. In this paper, we address the problem of copy-move forgery detection in JPEG images. The main problem with JPEG compression is that the same pixels, after moving to a different position and storing in the JPEG format, have different values. The majority of existing algorithms is based on matching pairs of similar patches, which generates many false matches. In many cases they cannot be eliminated by postprocessing, causing the failure of detection. To overcome this problem, we derive a JPEG-based constraint that any pair of patches must satisfy to be considered a valid candidate and propose an efficient algorithm to verify the constraint. The constraint can be integrated into most existing methods. Experiments show significant improvement of detection, especially for difficult cases, such as small objects, objects covered by textureless areas and repeated patterns. [ABSTRACT FROM AUTHOR]

The most common image tampering often for malicious purposes is to copy a region of the same image and paste to hide some other region. As both regions usually have same texture properties, therefore, this artifact is invisible for the viewers, and credibility of the image becomes questionable in proof centered applications. Hence, means are required to validate the integrity of the image and identify the tampered regions. Therefore, this study presents an efficient way of copy-move forgery detection (CMFD) through local binary pattern variance (LBPV) over the low approximation components of the stationary wavelets. CMFD technique presented in this paper is applied over the circular regions to address the possible post processing operations in a better way. The proposed technique is evaluated on CoMoFoD and Kodak lossless true color image (KLTCI) datasets in the presence of translation, flipping, blurring, rotation, scaling, color reduction, brightness change and multiple forged regions in an image. The evaluation reveals the prominence of the proposed technique compared to state of the arts. Consequently, the proposed technique can reliably be applied to detect the modified regions and the benefits can be obtained in journalism, law enforcement, judiciary, and other proof critical domains. [ABSTRACT FROM AUTHOR]

Forgery is an act of modifying a document, product, image or video, among other media. Video tampering detection research requires an inclusive database of video modification. This paper aims to discuss a comprehensive proposal to create a dataset composed of modified videos for forensic investigation, in order to standardize existing techniques for detecting video tampering. The primary purpose of developing and designing this new video library is for usage in video forensics, which can be consciously associated with reliable verification using dynamic and static camera recognition. To the best of the author's knowledge, there exists no similar library among the research community. Videos were sourced from YouTube and by exploring social networking sites extensively by observing posted videos and rating their feedback. The video tampering dataset (VTD) comprises a total of 33 videos, divided among three categories in video tampering: (1) copy-move, (2) splicing, and (3) swapping-frames. Compared to existing datasets, this is a higher number of tampered videos, and with longer durations. The duration of every video is 16s, with a 1280×720 resolution, and a frame rate of 30 frames per second. Moreover, all videos possess the same formatting quality (720p(HD).avi). Both temporal and spatial video features were considered carefully during selection of the videos, and there exists complete information related to the doctored regions in every modified video in the VTD dataset. This database has been made publically available for research on splicing, Swapping frames, and copy-move tampering, and, as such, various video tampering detection issues with ground truth. The database has been utilised by many international researchers and groups of researchers. [ABSTRACT FROM AUTHOR]

The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. [ABSTRACT FROM AUTHOR]

Audio forgery is any act of tampering, illegal copy and fake quality in the audio in a criminal way. In the last decade, there has been increasing attention to the audio forgery detection due to a significant increase in the number of forge in different type of audio. There are a number of methods for forgery detection, which electric network frequency (ENF) is one of the powerful methods in this area for forgery detection in terms of accuracy. In spite of suitable accuracy of ENF in a majority of plug-in powered devices, the weak accuracy of ENF in audio forgery detection for battery-powered devices, especially in laptop and mobile phone, can be consider as one of the main obstacles of the ENF. To solve the ENF problem in terms of accuracy in battery-powered devices, a combination method of ENF and phase feature is proposed. From experiment conducted, ENF alone give 50% and 60% accuracy for forgery detection in mobile phone and laptop respectively, while the proposed method shows 88% and 92% accuracy respectively, for forgery detection in battery-powered devices. The results lead to higher accuracy for forgery detection with the combination of ENF and phase feature. [ABSTRACT FROM AUTHOR]

Turquoise is frequently adulterated by unscrupulous dealers and, not rarely, simulants are commercialized as true stones. On the other hand, turquoise is a cryptocrystalline mineral and its use in adornments commonly demands some kind of treatment to facilitate its manipulation, such as impregnation using oil or fats, consolidation with resin and stabilization or reconstitution made with resins. In this work, Raman microscopy was employed in the investigation of turquoise adornments aiming to differentiate processed turquoise from fakes or simulants. Only one out of the five adornment objects analyzed was truly stabilized turquoise (powdered turquoise aggregated with a resin). Another one was constituted of turquoise, calcium carbonate, phthalocyanine blue and resin; the other objects were dyed minerals. [ABSTRACT FROM AUTHOR]

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II). [ABSTRACT FROM AUTHOR]

Forensic document examiners of Multiform Korean handwriting were tested using blind trials. A small number of experts (4) were tested for their performance and the test involved three steps. The participants each conducted a one-person examination first, then paired up with another person to perform the two-person examination and then finally the four people came together to conduct a group examination. When the experts actively exchanged opinions, the percentage of misleading decisions decreased while the percentage of inconclusive opinions increased. The deviations in the percentages of misleading results for different handwriting samples (long, short, signature) were not significant, while the disguised handwriting results showed the highest percentage of misleading conclusions. A special attention to artificially modified handwriting is therefore warranted rather than focusing on the number of letters. [ABSTRACT FROM AUTHOR]

Forensic handwriting examination is a relevant identification process in forensic science. This research obtained ideas from the process of features detection and analysis in forensic handwriting examination. A Chinese signature database was developed and comprised original signatures, freehand imitation forgeries, random forgeries and tracing imitation forgeries. The features of width, gray scale and radian combined with stroke orders were automatically extracted after image processing. A correlation coefficient was used to precisely characterize and express the similarities between signatures. To validate the differences between writers, a multivariate analysis of the variance was employed. The canonical discriminant analysis was performed between the original and non-original signatures; the cross-validation estimated the discriminating power of the width, gray scale and radian data. It is suggested that the extraction and analysis of these properties in Chinese signatures is reasonable. Meanwhile, forensic handwriting examination using the quantitative feature extraction and statistical analysis methods in this research could be performed with a satisfactory result in the discriminant analysis. [ABSTRACT FROM AUTHOR]

Object-based manipulations, such as adding or removing objects for digital video, are usually malicious forgery operations. Compared with the conventional double MPEG compression or frame-based tampering, it makes more sense to detect these object-based manipulations because they might directly affect our understanding towards the video content. In this paper, a passive video forensics scheme is proposed for object-based forgery operations. After extracting the adjustable width areas around object boundary, several statistical features such as the moment features of detailed wavelet coefficients and the average gradient of each colour channel are obtained and input into support vector machine (SVM) as feature vectors for the classification of natural objects and forged ones. Experimental results on several videos sequence with static background show that the proposed approach can achieve an accuracy of correct detection from 70% to 95%. [ABSTRACT FROM AUTHOR]

This paper presents a technique to discriminate the sequence of stamped seal impression and inkprinted text in a document to detect falsely signed documents. In many Asian countries where a seal is widely used to endorse documents, a possibly forged document involves a seal impressed before the text is printed. The proposed method uses adhesive tapes with peel adhesion strength of approximately 25 oz/in. to exfoliate the top layer of the overlapping region of seal impression and ink-printed text in the document. A pair of digital images of the overlapping region, captured using an infinite focus microscope, is compared for color changes before and after the exfoliation with adhesive tapes. The proposed sequence discrimination index (SDI) measures the amount of color changes before and after the exfoliation to determine the sequence of seal impression and printed text. Experiment results show that the SDI successfully discriminates the sequence of seal impression and printed text for different types of ink cartridges and seal inkpads under various storage conditions, enabling forensic investigation of falsely signed documents with a seal. [ABSTRACT FROM AUTHOR]

Determining the sequencing of intersecting ink lines is one of the current problems for forensic document examiners. The way two inks will distribute and interact with each other and the paper at the crossing is a dynamic process that can be affected by many variables. Thus, the main purpose of this manuscript is to visualize and have a more comprehensive understanding of this process as well as study a methodology for determining the correct order of intersecting ink lines. For this, overlapping layers of different types of inks from writing instruments and printers were cross-sectioned and examined with a microscope. Results from pen/pen crossings showed that liquid-liquid and gel-gel intersections tended to form a double layer but oil-oil intersections usually formed mixtures. Additionally, oil-liquid and oil- gel intersections tended to form a double layer whenever the oil ink was on top and liquid-gel intersections tended to form a double layer for almost all crossings with exception of the ones involving a gel pen ink from one manufacturer. Results from pen/printer crossings showed the formation of a double layer only when the printer ink was on top of the pen ink. On the other permutation, the pen ink tended to penetrate through the printer ink producing the mixture of both inks. The inks drying time was found to be an important factor affecting the interaction between two inks in a crossing, particularly crossings involving gel pen inks. On the contrary, the type of paper and the writing pressure showed no significant influence on the inks distribution at the crossing. The methodology developed was reproducible with overlapping layers but there were many experimental difficulties during the validation process of intersections representing real crossings. Moreover, interpretation was dependent on the operator's eye which was a limiting factor. [ABSTRACT FROM AUTHOR]

As powerful image editing tools are widely used, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the tampering techniques which are frequently used. Most existing techniques to expose this forgery need to improve the robustness for common postprocessing operations and fail to precisely locate the tampering region especially when there are large similar or flat regions in the image. In this paper, a robust method based on DCT and SVD is proposed to detect this specific artifact. Firstly, the suspicious image is divided into fixed-size overlapping blocks and 2D-DCT is applied to each block, then the DCT coefficients are quantized by a quantization matrix to obtain a more robust representation of each block. Secondly, each quantized block is divided nonoverlapping sub-blocks and SVD is applied to each sub-block, then features are extracted to reduce the dimension of each block using its largest singular value. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by predefined shift frequency threshold. Experiment results demonstrate that our proposed method can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, AWGN, JPEG compression and their mixed operations. [ABSTRACT FROM AUTHOR]

Questioned document examination in a wide variety of criminal and civil cases often focuses on the identification and comparison of stamp inks. Increasingly frequent counterfeiting of documents, especially those that have been stamped, has led to a growing need for instrumental methods that will allow an in-depth examination of stamp inks on a document. Therefore, the usefulness of two capillary electrophoresis techniques: micellar electrophoretic capillary chromatography with UV/Vis diode array detection (MECC-DAD) and capillary zone electrophoresis with electrospray mass spectrometric detection (CZE-ESI/MS) was verified for this purpose. Violet, red, blue and green stamp inks on paper surfaces were investigated. Electropherograms and mass spectra of inks purchased from 10 different producers were obtained in accordance with optimized and validated analytical procedures. It was shown that effective differentiation of individual inks was possible in terms of migration time and UV/ Vis spectra provided that there was more than one characteristic peak. However, the most problematic inks with only one very similar (or identical) dye component - violet and blue ones - were additionally differentiated by CZE-MS. The obtained results showed that the proposed procedures can be useful for the objective analysis of questioned documents involving stamp inks. Consequently, the developed methods can be applied in the forensic field, including in the investigation of the authenticity of documents. [ABSTRACT FROM AUTHOR]

False identity documents constitute a potential powerful source of forensic intelligence because they are essential elements of transnational crime and provide cover for organized crime. In previous work, a systematic profiling method using false documents' visual features has been built within a forensic intelligence model. In the current study, the comparison process and metrics lying at the heart of this profiling method are described and evaluated. This evaluation takes advantage of 347 false identity documents of four different types seized in two countries whose sources were known to be common or different (following police investigations and dismantling of counterfeit factories). Intra-source and inter-sources variations were evaluated through the computation of more than 7500 similarity scores. The profiling method could thus be validated and its performance assessed using two complementary approaches to measuring type I and type II error rates: a binary classification and the computation of likelihood ratios. Very low error rates were measured across the four document types, demonstrating the validity and robustness of the method to link documents to a common source or to differentiate them. These results pave the way for an operational implementation of a systematic profiling process integrated in a developed forensic intelligence model. [ABSTRACT FROM AUTHOR]

This paper describes the development and validation of a method for the analysis of office papers by measuring carbon isotopes using isotope ratio mass spectrometry (IRMS). The method development phase included testing protocols for storage, sample materials, set-up of the analytical run; and examining the effects of other paper examination procedures on IRMS results. A method validation was performed so that the Deltaplus XP IRMS instrument (Thermo Finnigan, Bremen, Germany) with Flash EA™ 1112 could be used to measure document paper samples for forensic casework. A validation protocol that would meet international standards for laboratory accreditation (international standard ISO 17025) was structured so that the instruments performance characteristics could be observed. All performance characteristics measured were found to be within an acceptable range and an expanded measurement uncertainty for the measurement of carbon isotopes in paper was calculated at 0.26‰, with a coverage factor of 2. This method was utilized in a large-scale study, published as part one of this series, that showed that IRMS of document papers is useful as a chemical comparison technique for 80 gsm white office papers. [ABSTRACT FROM AUTHOR]

Currently, digital images and videos have high importance because they have become the main carriers of information. However, the relative ease of tampering with images and videos makes their authenticity untrustful. Digital image forensics addresses the problem of the authentication of images or their origins. One main branch of image forensics is passive image forgery detection. Images could be forged using different techniques, and the most common forgery is the copy-move, in which a region of an image is duplicated and placed elsewhere in the same image. Active techniques, such as watermarking, have been proposed to solve the image authenticity problem, but those techniques have limitations because they require human intervention or specially equipped cameras. To overcome these limitations, several passive authentication methods have been proposed. In contrast to active methods, passive methods do not require any previous information about the image, and they take advantage of specific detectable changes that forgeries can bring into the image. In this paper, we describe the current state-of-the-art of passive copy-move forgery detection methods. The key current issues in developing a robust copy-move forgery detector are then identified, and the trends of tackling those issues are addressed. [ABSTRACT FROM AUTHOR]

Copy-move forgery is one of the most popular tampering artifacts in digital images. In this paper, we present an efficient method for copy-move forgery detection using Multiresolution Local Binary Patterns (MLBP). The proposed method is robust to geometric distortions and illumination variations of duplicated regions. Furthermore, the proposed block-based method recovers parameters of the geometric transformations. First, the image is divided into overlapping blocks and feature vectors for each block are extracted using LBP operators. The feature vectors are sorted based on lexicographical order. Duplicated image blocks are determined in the block matching step using k-d tree for more time reduction. Finally, in order to both determine the parameters of geometric transformations and remove the possible false matches, RANSAC (RANdom SAmple Consensus) algorithm is used. Experimental results show that the proposed approach is able to precisely detect duplicated regions even after distortions such as rotation, scaling, JPEG compression, blurring and noise adding. [ABSTRACT FROM AUTHOR]

Copy-move is one of the most commonly used image tampering operation, where a part of image content is copied and then pasted to another part of the same image. In order to make the forgery visually convincing and conceal its trace, the copied part may subject to post-processing operations such as rotation and blur. In this paper, we propose a polar cosine transform and approximate nearest neighbor searching based copy-move forgery detection algorithm. The algorithm starts by dividing the image into overlapping patches. Robust and compact features are extracted from patches by taking advantage of the rotationally-invariant and orthogonal properties of the polar cosine transform. Potential copy-move pairs are then detected by identifying the patches with similar features, which is formulated as approximate nearest neighbor searching and accomplished by means of locality-sensitive hashing (LSH). Finally, post-verifications are performed on potential pairs to filter out false matches and improve the accuracy of forgery detection. To sum up, the LSH based similar patch identification and the post-verification methods are two major novelties of the proposed work. Experimental results reveal that the proposed work can produce accurate detection results, and it exhibits high robustness to various post-processing operations. In addition, the LSH based similar patch detection scheme is much more effective than the widely used lexicographical sorting. [ABSTRACT FROM AUTHOR]

Abstract: Region duplication forgery is one of the tampering techniques that are frequently used, where a part of an image is copied and pasted into another part of the same image. In this paper, a phase correlation method based on polar expansion and adaptive band limitation is proposed for region duplication forgery detection. Our method starts by calculating the Fourier transform of the polar expansion on overlapping windows pair, and then an adaptive band limitation procedure is implemented to obtain a correlation matrix in which the peak is effectively enhanced. After estimating the rotation angle of the forgery region, a searching algorithm in the sense of seed filling is executed to display the whole duplicated region. Experimental results show that the proposed approach can detect duplicated region with high accuracy and robustness to rotation, illumination adjustment, blur and JPEG compression while rotation angle is estimated precisely for further calculation. [Copyright &y& Elsevier]

Abstract: This paper describes a method for verifying the authenticity of a seal impression imprinted on a document based on the seal overlay metric, which refers to the ratio of an effective seal impression pattern and the noise in the neighborhood of the reference impression region. A reference seal pattern is obtained by taking the average of a number of high-quality impressions of a genuine seal. A target seal impression to be examined, often on paper with some background texts and lines, is segmented out from the background by an adaptive threshold applied to the histogram of color components. The segmented target seal impression is then spatially aligned with the reference by maximizing the count of matching pixels. Then the seal overlay metric is computed for the reference and the target. If the overlay metric of a target seal is below a predetermined limit for the similarity to the genuine, then the target is classified as a forged seal. To further reduce the misclassification rate, the seal overlay metric is adjusted by the filling rate, which reflects the quality of inked pattern of the target seal. Experiment results demonstrate that the proposed method can detect elaborate seal impressions created by advanced forgery techniques such as lithography and computer-aided manufacturing. [Copyright &y& Elsevier]

Abstract: With the availability of the powerful editing software and sophisticated digital cameras, region duplication is becoming more and more popular in image manipulation where part of an image is pasted to another location to conceal undesirable objects. Most existing techniques to detect such tampering are mainly at the cost of higher computational complexity. In this paper, we present an efficient and robust approach to detect such specific artifact. Firstly, the original image is divided into fixed-size blocks, and discrete cosine transform (DCT) is applied to each block, thus, the DCT coefficients represent each block. Secondly, each cosine transformed block is represented by a circle block and four features are extracted to reduce the dimension of each block. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by a preset threshold value. In order to make the algorithm more robust, some parameters are proposed to remove the wrong similar blocks. Experiment results show that our proposed scheme is not only robust to multiple copy-move forgery, but also to blurring or nosing adding and with low computational complexity. [Copyright &y& Elsevier]

Abstract: Techniques for digital image tampering are becoming more and more sophisticated and widespread. Copy-move forgery is one of the tampering techniques that are frequently used. In this paper, an improved DCT-based method is developed to detect this specific artifact. Firstly, the image is divided into fixed-size overlapping blocks and, DCT is applied to each block to represent its features. Truncating is employed to reduce the dimension of the features. Then the feature vectors are lexicographically sorted and, duplicated image blocks will be neighboring in the sorted list. Thus duplicated image blocks will be compared in the matching step. To make the method more robust, a scheme to judge whether two feature vectors are similar is imported. Experiment results demonstrated that the proposed method can detect the duplicated regions even when an image was distorted by JPEG compression, blurring or additive white Gaussian noise. [Copyright &y& Elsevier]

Abstract: In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human–computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of forgery called copy–move forgery. The method is based on blur moment invariants, which allows successful detection of copy–move forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy–move forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy–move forgery. [Copyright &y& Elsevier]

Identification of individual by signature examination could be improved by the lateral palm print examination. By the use of new technique discussed by the author in this paper, the forensic expert can find out very useful information about the writer of writings even without going into the depth of questioned document/signature examination and without the formal or informal handwriting exemplars. The document expert with little more knowledge of the palm print can identify whether the signature is done by hand/leg/anything else, whether the author is right handed or left handed, the approximate age of the author, whether the signature is genuine or forged. Such information of author would be very much useful in elimination of the list of suspects of anonymous letters. In order to fix the authorship, standard and disputed lateral palm prints can be examined either with photographic superimposition technique or with the statistical study of the outline of the lateral palm print or with the standard method as implied in fingerprint examination. The evidential value of such lateral palm print can be placed at par with the finger prints in the court of law and could be placed right on the top of all other scientific evidences. [Copyright &y& Elsevier]