Advances in the field of Information Technology also make Information Security an inseparable part of it. In order to deal with security, Authentication plays an important role. This paper presents a review on the biometric authentication techniques and some future possibilities in this field. In biometrics, a human being needs to be identified based on some characteristic physiological parameters. A wide variety of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user, and not anyone else. By using biometrics it is possible to confirm or establish an individual’s identity. The position of biometrics in the current field of Security has been depicted in this work. We have also outlined opinions about the usability of biometric authentication systems, comparison between different techniques and their advantages and disadvantages in this paper.

Biometric Authentication: A Review

CITATION: Grobler, L. et al. 2016. Nutritional supplements for people being treated for active tuberculosis. Cochrane Database of Systematic Reviews, 6:CD006086, doi:10.1002/14651858.CD006086.pub4.

Nutritional supplements for people being treated for active tuberculosis

The Hammersmith Infant Neurological Examination (HINE) has been proposed as one of the early neurological examination tools for the diagnosis of cerebral palsy (CP). The aim of the present study was to critically review the existing literature and our experience with the use of the HINE in infants at risk of CP. The published papers confirm that the HINE can play an important role in the diagnosis and prognosis of infants at risk of developing CP, and provide information on aspects of neurological findings impaired in different forms of CP and brain lesions.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/dmcn.12876

Use of the Hammersmith Infant Neurological Examination in infants with cerebral palsy: a critical review of the literature

The prevalence and predisposing factors of thrombotic microangiopathy (TMA) in the era of highly active antiretroviral therapy (HAART) were evaluated among patients in the Collaborations in Human Immunodeficiency Virus (HIV) Outcomes Research/US cohort. Of 6022 patients, 17 (0.3%) had TMA, with unadjusted incidences per 100 person-years of 0.079 for TMA, 0.009 for thrombotic thrombocytopenic purpura, and 0.069 for hemolytic-uremic syndrome. Compared with patients without TMA, patients with TMA had lower mean CD4(+) cell counts (197 vs. 439 cells/mm(3); P=.0009) and higher mean log(10) HIV-1 RNA levels (4.6 vs. 3.3 copies/mL; P=.0001) at last follow-up and a significantly greater incidence of acquired immune deficiency syndrome (82.4% vs. 55.3%; P=.025), Mycobacterium avium complex infection (17.6% vs. 3.3%; P=.018), hepatitis C (29.4% vs. 11.3%; P=.001), and death (41.2% vs. 7.4%; P<.0001). The prevalence of herpes and use of antiherpetics were slightly higher for patients with TMA, but unadjusted distributions were not statistically significant. TMA in a cohort surveyed after the introduction of HAART was rare and was associated with advanced HIV disease.

https://www.jstor.org/stable/pdfplus/4462963.pdf

HIV-Associated Thrombotic Microangiopathy in the Era of Highly Active Antiretroviral Therapy: An Observational Study

Biometrics can be classified into two types Behavioral (signature verification, keystroke dynamics, etc.) and Physiological (iris characteristics, fingerprint, etc.). Handwritten signature is one of the first few biometrics used even before computers. Signature verification is widely studied and discussed using two approaches. On-line approach and offline approach. Offline systems are more applicable and easy to use in comparison with on-line systems in many parts of the world however it is considered more difficult than on-line verification due to the lack of dynamic information. This paper presents the State-of-the-Art about offline signature verification system; this biometric identification method that had more attraction in recent years because of its necessity for use in daily life routines and when the signature needs to be immediately verified like bank checks. In this paper, we present signature forgery types, features types and recent methods used for features extraction in signature verification systems and approaches used for verification in signature systems. Then we discuss these approaches and for which type of forgeries its suitable. Finally, we suggest new interesting ideas to be incorporated in the future.

State-of-the-art in offline signature verification system

Signatures were considered an important tool for authenticating the identity of human beings. So, signature verification was one of the biggest uses for that. We proposed an algorithmic approach for the verification of handwritten signatures by applying some statistical methods. The research work was based on the collection of set of signatures from which an average signature was obtained based on our algorithm and then taking decision of acceptance after analyzing the correlation in between the sample signature and the average signature.

Statistical Approach for Offline Handwritten Signature Verification

In this paper, a new technique for hiding the data of images has been proposed This method is invented to hide an image file entirely with in another image file keeping two considerations in mind which are Size and Degree of Security At the source, the image which is to be hidden (target image) is encoded at the end of another image (cover image) Double layer security of the hidden image can be achieved (over the untrusted network) by; firstly, the starting point of encoding the image data is depended on the size of the images and it is stored within the encoded image at the end of its header information as a cipher text; secondly, the target image is hidden behind the cover image by following our encrypted image hiding technique

A Secured Technique for Image Data Hiding

The dynamic growth in the field of Information communication has hiked the ease of Information transmission. But this type of real advancement in other sense has explored so many possibilities of information being snooped, at the time of communication in between the sender and the intended receiver. So, day by day Information Security is becoming an inseparable part of Computing and Communication. Various tools are available in order to address those issues and in them Steganography plays a significant role. In this paper, a heuristic approach for Information hiding in the form of multimedia objects or text using Steganography is proposed keeping in mind two considerations - Size and degree of security. Here, the Information is hidden behind an image in the form of an encoded matrix which is obtained from the bit matrix of the embedded object.

A Secure Scheme for Image Transformation

Image clustering and categorization is a means for high-level description of image content. In the field of content-based image retrieval (CBIR), the analysis of gray scale images has got very much importance because of its immense application starting from satellite images to medical images. But the analysis of an image with such number of gray shades becomes very complex, so, for simplicity we cluster the image into a lesser number of gray levels. Using K-Means clustering algorithm we can cluster an image to obtain segments. The main disadvantage of the k-means algorithm is that the number of clusters, K, must be supplied as a parameter. Again, this method does not specify the optimal cluster number. In this paper, we have provided a mathematical approach to determine the optimal cluster number of a clustered grayscale images. A simple index, based on the intra-cluster and inter-cluster distance measures has been proposed in this paper, which allows the number of clusters to be determined automatically.

A Novel Approach for Determination of Optimal Number of Cluster

Hammersmith Infant Neurological Examination (HINE) is a set of tests used for grading neurological development of infants on a scale of 0 to 3. These tests help in assessing neurophysiological development of babies, especially preterm infants who are born before (the fetus reaches) the gestational age of 36 weeks. Such tests are often conducted in the follow-up clinics of hospitals for grading infants with suspected disabilities. Assessment based on HINE depends on the expertise of the physicians involved in conducting the examinations. It has been noted that some of these tests, especially pulled-to-sit and lateral tilting, are difficult to assess solely based on visual observation. For example, during the pulled-to-sit examination, the examiner needs to observe the relative movement of the head with respect to torso while pulling the infant by holding wrists. The examiner may find it difficult to follow the head movement from the coronal view. Video object tracking based automatic or semi-automatic analysis can be helpful in this case. In this paper, we present a video based method to automate the analysis of pulled-to-sit examination. In this context, a dynamic programming and node pruning based efficient video object tracking algorithm has been proposed. Pulled-to-sit event detection is handled by the proposed tracking algorithm that uses a 2-D geometric model of the scene. The algorithm has been tested with normal as well as marker based videos of the examination recorded at the neuro-development clinic of the SSKM Hospital, Kolkata, India. It is found that the proposed algorithm is capable of estimating the pulled-to-sit score with sensitivity (80%-92%) and specificity (89%-96%).

Swarnendu Mukherjee

Papers

Statistical Approach for Offline Handwritten Signature Verification

A Secured Technique for Image Data Hiding

A Secure Scheme for Image Transformation

A Novel Approach for Determination of Optimal Number of Cluster

Toward Automating Hammersmith Pulled-To-Sit Examination of Infants Using Feature Point Based Video Object Tracking