A Survey on Methods of Image Processing and Recognition for Personal Identification

The network of blood vessels possesses several properties that make a good biometric feature for personal identification: (1) they are difficult to damage and modify; (2) they are difficult to simulate using a fake template; and (3) vein information can represent the liveness of the person. In the process of recognition of the network of blood vessels, we encounter two main difficulties: the first difficulty concerns the enhancement of the image of blood vessels obtained from the camera working in visible and/or infrared light, and the second one concerns the process of extraction of features and methods of classification. In the first part, this chapter presents the basic methods of preprocessing biometric images. In the second part, we discuss the process of feature extraction with particular emphasis on the feature extraction from images depicting the network of blood vessels. This applies to texture analysis using the co-occurrence matrix, Gabor filtration, moments, and topological features using cross points. In the third part, we present the methods of processing images of the blood vessel network of dorsal part of the hand and wrist. We also discuss the process of reducing the dimensionality of a feature vector using the principal components analysis method

Visual Tracking Based on Human Feature Extraction from Surveillance Video for Human Recognition

A multimodal human identification system based on face and body recognition may be made available for effective biometric authentication. The outcomes are achieved by extracting facial recognition characteristics using several extraction techniques, including Eigen-face and Principle Component Analysis (PCA). Systems for authenticating people using their bodies and faces are implemented using artificial neural networks (ANN) and genetic optimization techniques as classifiers. Through feature fusion and scores fusion, the biometric systems for the human body and face are merged to create a single multimodal biometric system. Human bodies may be identified with astonishing accuracy and effectiveness thanks to the SDK for the Kinect sensor. To identify people, biometrics aims to mimic the pattern recognition process. In comparison to traditional authentication methods based on secrets and tokens, it is a more dependable and safe option. Human physiological and behavioral traits are used by biometric technologies to identify people automatically. These characteristics must fulfill many criteria, especially those that relate to universality, efficacy, and applicability

The effect of work related mechanical stress on the peripheral temperature of the hand

The evolution and developments in modern industry have resulted a wide range of occupational activities, some of which can lead to industrial injuries. Due to the activities of occupational medicine, much progress has been made in transforming the way that operatives perform their tasks. However there are still many occupations where manual tasks have become more repetitive, contributing to the development of conditions that affect the upper limbs. Repetitive Strain Injury is one classification of those conditions which is related to overuse of repetitive movement. Hand Arm Vibration Syndrome is a subtype of this classification directly related to the operation of instruments and machinery which involves vibration. These conditions affect a large number of individuals, and are costly in terms of work absence, loss of income and compensation. While such conditions can be difficult to avoid, they can be monitored and controlled, with prevention usually the least expensive solution. In medico-legal situations it may be difficult to determine the location or the degree of injury, and therefore determining the relevant compensation due is complicated by the absence of objective and quantifiable methods. This research is an investigation into the development of an objective, quantitative and reproducible diagnostic procedure for work related upper limb disorders. A set of objective mechanical provocation tests for the hands have been developed that are associated with vascular challenge. Infrared thermal imaging was used to monitor the temperature changes using a well defined capture protocol. Normal reference values have been measured and a computational tool used to facilitate the process and standardise image processing. These objective tests have demonstrated good discrimination between groups of healthy controls and subjects with work related injuries but not individuals, p<0.05, and are reproducible. A maximum value for thermal symmetry of 0.5±0.3ºC for the whole upper limbs has been established for use as a reference. The tests can be used to monitor occupations at risk, aiming to reduce the impact of these conditions, reducing work related injury costs, and providing early detection. In a medico-legal setting this can also provide important objective information in proof of injury and ultimately in objectively establishing whether or not there is a case for compensation

Pattern mining approaches used in sensor-based biometric recognition: a review

Sensing technologies place significant interest in the use of biometrics for the recognition and assessment of individuals. Pattern mining techniques have established a critical step in the progress of sensor-based biometric systems that are capable of perceiving, recognizing and computing sensor data, being a technology that searches for the high-level information about pattern recognition from low-level sensor readings in order to construct an artificial substitute for human recognition. The design of a successful sensor-based biometric recognition system needs to pay attention to the different issues involved in processing variable data being - acquisition of biometric data from a sensor, data pre-processing, feature extraction, recognition and/or classification, clustering and validation. A significant number of approaches from image processing, pattern identification and machine learning have been used to process sensor data. This paper aims to deliver a state-of-the-art summary and present strategies for utilizing the broadly utilized pattern mining methods in order to identify the challenges as well as future research directions of sensor-based biometric systems

Dorsal hand vein image enhancement using fusion of clahe and fuzzy adaptive gamma

Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique’s impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins

The use of infrared thermal imaging as a marker of tissue perfusion and predictor of arteriovenous fistula outcomes

The gold standard of vascular access is the arteriovenous fistula (AVF). Unfortunately it is associated with high rates of failing to mature. Therefore the ability to predict AVF outcomes would change clinical practice. Predictive markers of AVF outcomes were assessed in chapter 2. The literature and our study showed numerous contradictions. In chapter 3 we assessed a multifactorial approach with a systematic review on predictive models of maturation. The review found few models and the disparity between each one limits the development of a unified model. Recent development in infrared thermal imaging (IRTI) technology has made it portable and easy to use. In Chapter 4, we proved that IRTI is a valid and user-friendly method of measuring skin temperature and is comparable to traditional methods of thermometry. IRTI can be used to quantity reactive hyperaemia following a vascular occlusion test (chapter 5). In Chapter 6 we showed that IRTI is an accurate tool in predicting AVF outcome. It was shown to have superiority to intra-operative thrill and other independent patient factors. In conclusion IRTI has a definite role in patients with vascular access. There is also potential for its use in patients with other conditions such as peripheral vascular disease