Septimiu Crisan

Radiation optimization and image processing algorithms in the identification of hand vein patterns

Vein pattern recognition is one of the newest biometric techniques researched today. While the concept behind the method is simple, there are various challenges to be found throughout the design and implementation of a vein-scanning device concerning the lighting system and the image processing algorithms. To achieve low scanning errors, the acquired image should be almost noiseless and the algorithms should detect the vein pattern in various conditions. Many implementations of this method are now in a commercial phase and there is a great need for low cost systems that can detect human veins with minimum computational requirements.

Optical Multi-touch System for Patient Monitoring and Medical Data Analysis

One of the greatest challenges in medical environments nowadays is finding a way to collect and display vital patient data for monitoring and diagnosis purposes. While communication and image storage standards such as DICOM do exist, the relevant data is still split up between different workstations and proprietary visualization equipments. Multi-touch, multi-user display devices can bring an important contribution to collaborative medical work and can also act as an administrative tool for hospitals. Based on our previous research, a high resolution optical multi-touch system has been implemented where relevant medical data can be visualized and manipulated through intuitive finger movements without the need of standard computer peripherals. A full set of software applications for this purpose has been designed in order to test the viability of this method.

Image Analysis and Coding Based on Ordinal Data Representation

With the use of computers and Internet in every major activity of our society, security is increasingly important. Biometric recognition is not only challenging but also computationally demanding. This chapter aims develop an iris biometric system. The iris has the advantages of uniqueness, stableness, anti-spoof, non-invasiveness and efficiency and could be applied in almost every area (banking, forensics, access control, etc.). The performance of a biometric classification system is largely depending on the techniques used for feature extraction. Inspired by the biological plausibility of ordinal measures, we propose their employment for iris representation and recognition. Qualitative measurement, associated to the relative ordering of different characteristics, is defined as ordinal measurement. Besides the proposing of a novel, fast and robust, ordinal based feature extraction method, the chapter also considers the problem of designing the decision making model so as to obtain an efficient and effective biometric system. In the literature, there are different approaches for iris recognition, nevertheless, there are still challenging open problems in improving the accuracy, robustness, security and ergonomics of biometric systems.

Optimization of a multi-touch sensing device for biomedical applications

Multi-touch systems are redefining the natural user interface paradigm and their applications can be found ranging from mobile phones, tablets and screens to the control of industrial facilities. While the concepts of multiple touch sensing are not new, there are still large unexplored areas regarding optimization of the user experience for various industrial or medical applications. Along with the ability to detect and process simultaneous touches and gestures, large scale multi-touch devices offer collaborative work along with user-selective content management systems features rarely used in dedicated medical visualization or sensing multi-touch software applications. Based on previous research concerning multi-touch systems and their potential usefulness in the medical field, this paper describes the optimization process of a multi-touch sensing device for biomedical applications. Three important layers of a multi-touch device were chosen as candidates for optimization: sensing, data manipulation and visualization. The results were applied to a prototype optical touch system developed for multi-user/multi-touch environments and several hardware and software modifications were designed and implemented. Since the goal of this research was to explore ways to enhance the user experience in multi-touch applications the conclusions derived from this paper can be extended to other domains where concurrent visualization and processing of information are vital components.

A Novel Perspective on Hand Vein Patterns for Biometric Recognition: Problems, Challenges, and Implementations

Biometric recognition using hand vein patterns is a relatively new technology that has showed a lot of promise from its inception, with features matching or even exceeding well-established biometric methods. Parameters such as universality, permanence, degree of acceptance, or collectability place vein pattern recognition in the top echelon of biometric methods and still, the technology has not gained the traction heralded in the beginning. The novelty of the domain and the low-entry price point for developing hardware scanning devices have created an opposite effect, where the lack of standardization, low amount of usable hand vein samples, and the over-optimization of the detection algorithms have not yielded significant practical solutions for mainstream integration of the technology. The chapter addresses hand vein patterns—with an emphasis on the veins on the back of the hand—and contains a combination of novel research and analysis/discussion regarding the state of hand vein pattern recognition, its challenges, and potential modern approaches for mitigating the inherent problems of the technology. Closing remarks attempt to picture a possible future roadmap for vein pattern recognition and its inclusion in a permanently connected world.

3D Simulation Analysis of Transcranial Magnetic Stimulation

This paper presents the results from a simulation of Transcranial Magnetic Stimulation using realistic brain model. The simulation found some interesting results regarding the distribution of the electric field induced in the cortex.

Hand Vein Biometric Authentication in Optical Multi-touch Systems

Multi-touch systems and their applications are entering a mainstream phase where fast access to visual data and collaborative environments are key factors for an informational age. However, most systems are envisioned as public workstations where resources are shared equally between the users with few or no restrictions on the content delivered by the applications. While real-time identification of the users of a multi-touch system is a difficult subject to tackle, authentication using biometric parameters could provide a hierarchy based content management system. Based on previous research in both hand vein biometric detection and multi-touch systems, this paper describes a hand vein authentication device usable in a touch/object sensing multi-user collaborative environment.

Iris indexing based on local intensity order pattern.

In recent years, iris biometric systems have increased in popularity and have been proven that are capable of handling large-scale databases. The main advantage of these systems is accuracy and reliability. A proper iris patterns classification is expected to reduce the matching time in huge databases. This paper presents an iris indexing technique based on Local Intensity Order Pattern. The performance of the present approach is evaluated on UPOL database and is compared with other recent systems designed for iris indexing. The results illustrate the potential of the proposed method for large scale iris identification.

Dorsal hand vein recognition based on Riesz Wavelet Transform and Local Line Binary Pattern

Biometrics has been widely used in the last decades for security purposes and for increasing the confidence of people in the new informational systems. The present paper presents a new analysis and encoding method of dorsal hand vein patterns, for biometric recognition. Two multiresolution approaches, Discrete Wavelet Transform and Riesz Wavelet Transform, are firstly applied to extract directional image features. The resulted coefficients are encoded based on an ordinal procedure, namely Local Line Binary Pattern.

Prefrontal cortex magnetic stimulation, a simulation analysis

The presented work aims to elucidate where stimulation occurs in the brain during transcranial magnetic stimulation (TMS), taking into account cortical geometry. A realistic computer model of TMS was developed comprising a stimulation coil and the human cortex. The coil was positioned over the right dorsolateral prefrontal cortex (right DLPFC) and the distribution of the induced electric field was analyzed. A computer simulation was constructed, where the coil is positioned at an angle of 450 relative to the sagittal plane. The results highlight the influence of cortical geometry on the distribution of the electric field in the brain and show that the highest values are not obtained directly under the center of the stimulator.