Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition

Biometric identification is highly reliable for human identification. Biometric is a field of science used for analyzing the physiological or behavioural characteristics of human. Iris features are unique, stable and can be visible from longer distances. It uses mathematical pattern-recognition techniques on video images of one or both iris of an individual's. Compared to other biometric traits, iris is more challenging and highly secured tool to identify the individual. In this paper iris recognition based on the combination of Discrete Wavelet Transform (DWT), Inverse Discrete Wavelet Transform (IDWT), Independent Component Analysis (ICA) and Binariezed Statistical Image Features (BSIF) are adopted to generate the hybrid iris features. The first level and second level DWT are employed in order to extract the more unique features of the iris images. The concept of bicubic interpolation is applied on high frequency coefficients generated by first level decomposition of DWT to produce new set of sub-bands. The approximation band generated by second level decomposition of DWT and new set of sub-bands produced by second level decomposition of DWT are applied on IDWT to reconstruct the coefficients. The ICA 5x5 filters and BSIF are adopted for selecting the appropriate images to extract the final features. Finally based on the matching score between the database image and test image the genuine and imposters are identified. Using CASIA database, training and testing of the features is performed and performance is evaluated considering different combinations of Person inside Database (PID) and Person outside Database (POD).

Download Full-text

Performance Analysis of MSB Based Iris Recognition Using Hybrid Features Extraction Technique

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.e7292.088619 ◽

2019 ◽

Vol 8 (6) ◽

pp. 230-239 ◽

Cited By ~ 1

Keyword(s):

Euclidean Distance ◽

Iris Recognition ◽

Recognition Accuracy ◽

Image Features ◽

Discrete Wavelet ◽

Morphological Operations ◽

Physiological Trait ◽

Human Identity ◽

Hybrid Features ◽

Left And Right

In the modern days, biometric identification is more promising and reliable to verify the human identity. Biometric refers to a science for analyzing the human characteristics such as physiological or behavioral patterns. Iris is a physiological trait, which is unique among all the biometric traits to recognize an individual effectively. In this paper, MSB based iris recognition based on Discrete Wavelet Transform, Independent Component Analysis and Binariezed Statistical Image Features is proposed. The left and right region is extracted from eye images using morphological operations. Binary split is performed to divide the eight-bit binary of every pixel into four bit Least Significant Bits and four bit Most Significant Bits. DWT is applied on four bit MSB to extract the iris features. Then ICA is applied on approximate sub band to extract the significant details of iris. The obtained features are then applied on BSIF to obtain the enhanced response with final features. Finally features produced are matched with the test features using Euclidean distance classifier on CASIA database. The experiments are performed on proposed iris model using MATLAB 7.0 software considering various combinations of Person inside Database (PID’s) and Person outside Database (POD’s) to evaluate the recognition accuracy of the proposed iris model.

Download Full-text

Two-Tier Image Features Clustering for Iris Recognition on Mobile

Fuzzy Logic and Soft Computing Applications - Lecture Notes in Computer Science ◽

10.1007/978-3-319-52962-2_23 ◽

2017 ◽

pp. 260-269 ◽

Cited By ~ 3

Author(s):

Andrea F. Abate ◽

Silvio Barra ◽

Francesco D’Aniello ◽

Fabio Narducci

Keyword(s):

Iris Recognition ◽

Image Features

Download Full-text

Deep Learning-Based Enhanced Presentation Attack Detection for Iris Recognition by Combining Features from Local and Global Regions Based on NIR Camera Sensor

Sensors ◽

10.3390/s18082601 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2601 ◽

Cited By ~ 13

Author(s):

Dat Nguyen ◽

Tuyen Pham ◽

Young Lee ◽

Kang Park

Keyword(s):

Iris Recognition ◽

Near Infrared ◽

Recognition Rate ◽

Image Features ◽

Attack Detection ◽

Support Vector ◽

Security Level ◽

Iris Patterns ◽

Presentation Attack Detection ◽

Camera Sensor

Iris recognition systems have been used in high-security-level applications because of their high recognition rate and the distinctiveness of iris patterns. However, as reported by recent studies, an iris recognition system can be fooled by the use of artificial iris patterns and lead to a reduction in its security level. The accuracies of previous presentation attack detection research are limited because they used only features extracted from global iris region image. To overcome this problem, we propose a new presentation attack detection method for iris recognition by combining features extracted from both local and global iris regions, using convolutional neural networks and support vector machines based on a near-infrared (NIR) light camera sensor. The detection results using each kind of image features are fused, based on two fusion methods of feature level and score level to enhance the detection ability of each kind of image features. Through extensive experiments using two popular public datasets (LivDet-Iris-2017 Warsaw and Notre Dame Contact Lens Detection 2015) and their fusion, we validate the efficiency of our proposed method by providing smaller detection errors than those produced by previous studies.

Download Full-text

7-beam lattice images of (110) oriented Ge

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100108593 ◽

1978 ◽

Vol 36 (1) ◽

pp. 290-291

Author(s):

J.R. Parsons ◽

C.W. Hoelke

Keyword(s):

Image Features ◽

Objective Lens ◽

Lattice Plane ◽

Lattice Image ◽

Crystalline Defects ◽

Transmission Electron ◽

Lattice Images ◽

Electron Microscopes ◽

Structural Aspects ◽

Beam Lattice

The direct imaging of a crystal lattice has intrigued electron microscopists for many years. What is of interest, of course, is the way in which defects perturb their atomic regularity. There are problems, however, when one wishes to relate aperiodic image features to structural aspects of crystalline defects. If the defect is inclined to the foil plane and if, as is the case with present 100 kV transmission electron microscopes, the objective lens is not perfect, then terminating fringes and fringe bending seen in the image cannot be related in a simple way to lattice plane geometry in the specimen (1).The purpose of the present work was to devise an experimental test which could be used to confirm, or not, the existence of a one-to-one correspondence between lattice image and specimen structure over the desired range of specimen spacings. Through a study of computed images the following test emerged.

Download Full-text

High-resolution electron microscopy of the atomic structure of some grain boundaries in Au

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100143663 ◽

1986 ◽

Vol 44 ◽

pp. 414-415

Author(s):

W. Krakow ◽

D. A. Smith

Keyword(s):

Atomic Structure ◽

High Resolution Electron Microscopy ◽

Image Features ◽

Image Feature ◽

Resolution Electron ◽

Tilt Boundaries ◽

Processing Techniques ◽

Atom Position ◽

Structure Configuration

The successful determination of the atomic structure of [110] tilt boundaries in Au stems from the investigation of microscope performance at intermediate accelerating voltages (200 and 400kV) as well as a detailed understanding of how grain boundary image features depend on dynamical diffraction processes variation with specimen and beam orientations. This success is also facilitated by improving image quality by digital image processing techniques to the point where a structure image is obtained and each atom position is represented by a resolved image feature. Figure 1 shows an example of a low angle (∼10°) Σ = 129/[110] tilt boundary in a ∼250Å Au film, taken under tilted beam brightfield imaging conditions, to illustrate the steps necessary to obtain the atomic structure configuration from the image. The original image of Fig. 1a shows the regular arrangement of strain-field images associated with the cores of ½ [10] primary dislocations which are separated by ∼15Å.

Download Full-text

Imaging of polymer single crystals in low-voltage, high-resolution scanning electron microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100178665 ◽

1990 ◽

Vol 48 (4) ◽

pp. 1106-1107

Author(s):

W.W. Adams ◽

G. Price ◽

A. Krause

Keyword(s):

Electron Microscopy ◽

Scanning Electron Microscopy ◽

High Resolution ◽

Single Crystals ◽

Low Voltage ◽

Polymer Surface ◽

Beam Current ◽

Image Features ◽

First Results ◽

Scanning Electron

It has been shown that there are numerous advantages in imaging both coated and uncoated polymers in scanning electron microscopy (SEM) at low voltages (LV) from 0.5 to 2.0 keV compared to imaging at conventional voltages of 10 to 20 keV. The disadvantages of LVSEM of degraded resolution and decreased beam current have been overcome with the new generation of field emission gun SEMs. In imaging metal coated polymers in LVSEM beam damage is reduced, contrast is improved, and charging from irregularly shaped features (which may be unevenly coated) is reduced or eliminated. Imaging uncoated polymers in LVSEM allows direct observation of the surface with little or no charging and with no alterations of surface features from the metal coating process required for higher voltage imaging. This is particularly important for high resolution (HR) studies of polymers where it is desired to image features 1 to 10 nm in size. Metal sputter coating techniques produce a 10 - 20 nm film that has its own texture which can obscure topographical features of the original polymer surface. In examining thin, uncoated insulating samples on a conducting substrate at low voltages the effect of sample-beam interactions on image formation and resolution will differ significantly from the effect at higher accelerating voltages. We discuss here sample-beam interactions in single crystals on conducting substrates at low voltages and also present the first results on HRSEM of single crystal morphologies which show some of these effects.

Download Full-text

Scientific Problem Solving in a Virtual Laboratory: A Comparison Between Individuals and Pairs

Swiss Journal of Psychology ◽

10.1024/1421-0185.67.2.71 ◽

2008 ◽

Vol 67 (2) ◽

pp. 71-83 ◽

Cited By ~ 5

Author(s):

Yolanda A. Métrailler ◽

Ester Reijnen ◽

Cornelia Kneser ◽

Klaus Opwis

Keyword(s):

Visual Search ◽

Problem Solving ◽

Process Data ◽

Scientific Problem ◽

Domain Specific ◽

Scientific Problem Solving ◽

Before And After ◽

Verbal Data ◽

Psychological Knowledge ◽

Problem Solving Task

This study compared individuals with pairs in a scientific problem-solving task. Participants interacted with a virtual psychological laboratory called Virtue to reason about a visual search theory. To this end, they created hypotheses, designed experiments, and analyzed and interpreted the results of their experiments in order to discover which of five possible factors affected the visual search process. Before and after their interaction with Virtue, participants took a test measuring theoretical and methodological knowledge. In addition, process data reflecting participants’ experimental activities and verbal data were collected. The results showed a significant but equal increase in knowledge for both groups. We found differences between individuals and pairs in the evaluation of hypotheses in the process data, and in descriptive and explanatory statements in the verbal data. Interacting with Virtue helped all students improve their domain-specific and domain-general psychological knowledge.

Download Full-text