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An almost unexplored research topic in visual secret sharing (VSS), i.e., sharing different visual secrets among various groups, is investigated in this article. Generally, multiple groups are cooperated together to encrypt multiple visual secrets, where every group is correlated with a VSS scheme to share one secret and each participant receives only one shadow. Such a cooperative system is referred to as cooperative VSS (CVSS). In this paper, we develop a general construction for CVSS with improved computational overhead. The basis matrices for generating the shadows are easily obtained. To improve the recovered image quality, an efficient XOR-based CVSS (XCVSS) is given. Furthermore, to fulfill the requirement of implementing complex sharing policy, the XCVSS is extended to collaborate general access structure (GAS) VSS schemes together. Theoretical and experimental results and comparisons are illustrated to demonstrate the advantages of the proposed techniques.

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

This paper presents a new scheme to implement an event-driven traffic ticketing system. The system consists of two modules, namely, (1) event detection module, (2) database management module to execute information retrieval and deliver traffic tickets. In this paper, the notable contribution is an automatic detection of traffic ticketing events from video footages and immediate notification of such event when a car is passing the white stop line before a red traffic light. The results show the authors' work is efficient and could detect the events precisely.

Nowadays, Biometrics has become a popular tool in personal identification as it can use physiological or behavioral characteristics to identify individuals. Recent advances in information technology has increased the accuracy of biometric to another level, there is still a slew of problems existed, such as complex environment, aging and unique problems. Among many classes of identifications, recognizing twins is one of the most difficult tasks as they resemble each other. This affects the use of biometrics in general cases and raises potential risks of biometrics in access control. In this paper, the authors manage to distinguish twins using four different models, namely, face recognition, ear recognition, voice recognition and lip movement recognition. Their results show that voice recognition has the best performance in twin recognition with 100% accuracy. This is much higher than that of face recognition and ear recognition (with 58% and 53% respectively); and lip movement recognition that yields 76% accuracy.

Repair of segmental bone defects remains a major challenge for orthopedic surgeons. This study aimed to investigate whether recombinant human bone morphogenetic protein-2 (rhBMP-2)-loaded calcium sulfate (CS) combined with mesenchymal stem cell (MSC) sheets could accelerate bone regeneration in ulnar segmental defects of rabbits. In vitro, the osteogenic differentiation of MSCs cultured on rhBMP-2-loaded CS was investigated. Forty complete 1.2-cm bone defects were treated with CS (group A), rhBMP-2-loaded CS (group B), MSC sheet-wrapped CS (group C), and MSC sheet-wrapped rhBMP-2-loaded CS (group D). At 4 and 8 weeks after implantation, the samples were treated by X-ray, microcomputed tomography, and histological observation. The rhBMP-2 could be released from the rhBMP-2-loaded CS scaffolds and maintain its bioactivity. The alkaline phosphatase (ALP) of MSCs cultured on rhBMP-2-loaded CS was significantly higher than that of CS at both 7 and 14 days (p< 0.05). The defects treated with MSC sheet-wrapped rhBMP-2-loaded CS showed significantly higher scores by X-ray analysis and more bone formation determined by both histology and microcomputed tomography than the other three groups at both 4 and 8 weeks after implantation (p< 0.05). No significant difference in X-ray score and bone formation was found between groups B and C, both significantly higher than group A (p< 0.05). The results suggested that MSC sheet-wrapped rhBMP-2-loaded CS may be an effective approach to promote the repair of segmental bone defects and has great potential for repairing large segmental bone defects in clinic.

In this paper, the authors splice together an image which has been split up on a piece of paper by using duplication detection. The nearest pieces are connected using edge searching and matching and the pieces that have graphics or textures are matched using the edge shape and intersection between the two near pieces. Thus, the initial step is to mark the direction of each piece and put the pieces that have straight edges to the initial position to determine the profile of the whole image. The other image pieces are then fixed into the corresponding position by using the edge information, i.e., shape, residual trace and matching, after duplication or sub-duplication detection. In the following steps, the patches with different edge shapes are searched using edge duplication detection. With the reduction of rest pieces, the montage procedure will become easier and faster.

In this paper, the authors investigate the prospect of using multi-resolution histograms (MRH) in conjunction with digital image forensics, particularly in the detection of two kinds of copy-move manipulations, i.e., cloning and splicing. To the best of the authors’ knowledge, this is the first work that uses the same feature in both cloning and splicing forensics. The experimental results show the simplicity and efficiency of using MRH for the purpose of clone detection and splicing detection.

This paper introduces a new technique for palmprint recognition based on Fisher Linear Discriminant Analysis (FLDA) and Gabor filter bank. This method involves convolving a palmprint image with a bank of Gabor filters at different scales and rotations for robust palmprint features extraction. Once these features are extracted, FLDA is applied for dimensionality reduction and class separability. Since the palmprint features are derived from the principal lines, wrinkles and texture along the palm area. One should carefully consider this fact when selecting the appropriate palm region for the feature extraction process in order to enhance recognition accuracy. To address this problem, an improved region of interest (ROI) extraction algorithm is introduced. This algorithm allows for an efficient extraction of the whole palm area by ignoring all the undesirable parts, such as the fingers and background. Experiments have shown that the proposed method yields attractive performances as evidenced by an Equal Error Rate (EER) of 0.03%.

This paper aims at digital watermark which is a new popular research topic recently, presents some methods to embed digital watermark based on modifying frequency coefficients in discrete wavelet transform (DWT) domain. First, the present progress of digital watermark is briefly introduced; after that, starting from Pitas’s method and discarding his pseudo random number method, the authors use a digital image scrambling technology as preprocessing for digital watermarking. Then the authors discuss how to embed a 1-bit digital image as watermark in frequency domain. Finally another digital watermarking method is given in which 3-D DWT is used to transform a given digital image. Based on the experimental results, it is shown that the proposed methods are robust to a large extent.

Background Severe traumatic brain injury (TBI) has been increasing with greater incidence of injuries from traffic or sporting accidents. Although there are a number of animal models of TBI using progesterone for head injury, the effects of progesterone on neurologic outcome of acute TBI patients remain unclear. The aim of the present clinical study was to assess the longer-term efficacy of progesterone on the improvement in neurologic outcome of patients with acute severe TBI.Methods A total of 159 patients who arrived within 8 hours of injury with a Glasgow Coma Score ≤ 8 were enrolled in the study. A prospective, randomized, placebo-controlled trial of progesterone was conducted in the Neurotrauma Center of our teaching hospital. The patients were randomized to receive either progesterone or placebo. The primary endpoint was the Glasgow Outcome Scale score 3 months after brain injury. Secondary efficacy endpoints included the modified Functional Independence Measure score and mortality. In a follow-up protocol at 6 months, the Glasgow Outcome Scale and the modified Functional Independence Measure scores were again determined.Results Of the 159 patients randomized, 82 received progesterone and 77 received placebo. The demographic characteristics, the mechanism of injury, and the time of treatment were compared for the two groups. After 3 months and 6 months of treatment, the dichotomized Glasgow Outcome Scale score analysis exhibited more favorable outcomes among the patients who were given progesterone compared with the control individuals (P = 0.034 and P = 0.048, respectively). The modified Functional Independence Measure scores in the progesterone group were higher than those in the placebo group at both 3-month and 6-month follow-up (P < 0.05 and P < 0.01). The mortality rate of the progesterone group was significantly lower than that of the placebo group at 6-month follow-up (P < 0.05). The mean intracranial pressure values 72 hours and 7 days after injury were lower in the progesterone group than in the placebo group, but there was no statistical significance between the two groups (P > 0.05). Instances of complications and adverse events associated with the administration of progesterone were not found.Conclusion Our data suggest that acute severe TBI patients with administration of progesterone hold improved neurologic outcomes for up to 6 months. These results provide information important for further large and multicenter clinical trials on progesterone as a promising neuroprotective drug.Trial Registration ACTRN12607000545460.