Figure 5 - uploaded by Samitha Nanayakkara
Content may be subject to copyright.
![Result after removal of eyelids and lashes from original image [10]](profile/Samitha-Nanayakkara/publication/339484562/figure/fig2/AS:862494960664578@1582646231589/Result-after-removal-of-eyelids-and-lashes-from-original-image-10.jpg)
Source publication
This paper presents a survey of literature related to the one of the biometric recognition systems-iris recognition system. Biometric authentication has become one of the important security technologies due to the prominent properties of biometrics compared to other authentication methods. Since most of the phenotypes of humans are unique, physiolo...
Contexts in source publication
Context 1
... using BLOB (Binary Large Object) analysis, strong edges will be selected as final edges. Finally, linear Hough transform will use to identify noise factors such as eyelids and lashes and Circular Hough transform will detect iris region like in Figure 5. ...
Context 2
... pattern separates to extract its information use these two Gabor filters. As shown in Figure 15, 2D iris pattern is divided into several 1D signals and then 1D signal convolve with 1D Gabor filter to get the response. Using Odd and even symmetric Gabor filters can obtain real response and imaginary response and then this phase information quantifies into four possible quadrant levels in complex plane. ...
Similar publications
Iris recognition is the most accurate form of biometric identification. The robustness of iris recognition
comes from the unique characteristics of the human iris texture as it is stable over the human life, and the
environmental effects cannot easily alter its shape. In most iris recognition systems, ideal image acquisition
conditions are assum...
![Fig. 1: Images from SDUMLA-HMT Dataset [3]](profile/Tonmoy-Hossain/publication/352789611/figure/fig1/AS:1042127618326528@1625473994019/Images-from-SDUMLA-HMT-Dataset-3_Q320.jpg)
Over the years Biometric authentication system
has gained widespread popularity due to the rising need for
personal identification and security. The most common biometric
features used in authentication systems are fingerprint, iris,
hand geometry, retina, finger vein, palm vein, and voice pattern.
Among them, finger vein biometric recognition syst...
span lang="EN-GB">A biometric system of identification and authentication provides automatic recognition of an individual based on certain unique features or characteristic possessed by an individual. Iris recognition is a biometric identification method that uses pattern recognition on the images of the iris. Owing to the unique epigenetic pattern...
Iris recognition is a widely used biometric identification technology that relies on the accurate and efficient matching of iris images. However, fast matching in large databases poses a significant challenge due to the increasing search time for a given query. To address this problem, this paper proposes an end-to-end hashing framework for iris re...
The biometric verification is necessary for the identification of human subjects for the purpose of security and authentication. Biometric data are very much unambiguous to each one, easily obtainable non-intrusively, no significant changes over a period of time and detectable by humans without much special training. Biometric traits provide a uniq...
Citations
... In the following part, we evaluate these reviews and point out how our work differs from theirs. [8][9][10] summarize the basic IR process according to the traditional biometric recognition workflow, including image acquisition, pre-processing, image segmentation, feature extraction, and classification. In [8,9], in addition to these above steps, image normalization is also introduced. ...
... [8][9][10] summarize the basic IR process according to the traditional biometric recognition workflow, including image acquisition, pre-processing, image segmentation, feature extraction, and classification. In [8,9], in addition to these above steps, image normalization is also introduced. Meanwhile, these reviews introduce machine learning-based approaches instead of focusing on deep learning methods, which cannot provide a comprehensive insight into the current deep learning-based mainstream. ...
... Meanwhile, these reviews introduce machine learning-based approaches instead of focusing on deep learning methods, which cannot provide a comprehensive insight into the current deep learning-based mainstream. Specifically, [8] mentions neural network techniques in the feature extraction and classification phases, and [9] briefly summarizes the application of CNNs in the iris image segmentation and feature extraction phases, but there is not a comprehensive and systematic summary of deep learning techniques. Additionally, reviews [9,10] lack the summary of influential public IR datasets. ...
Iris recognition is a secure biometric technology known for its stability and privacy. With no two irises being identical and little change throughout a person's lifetime, iris recognition is considered more reliable and less susceptible to external factors than other biometric recognition methods. Unlike traditional machine learning-based iris recognition methods, deep learning technology does not rely on feature engineering and boasts excellent performance. This paper collects 120 relevant papers to summarize the development of iris recognition based on deep learning. We first introduce the background of iris recognition and the motivation and contribution of this survey. Then, we present the common datasets widely used in iris recognition. After that, we summarize the key tasks involved in the process of iris recognition based on deep learning technology, including identification, segmentation, presentation attack detection, and localization. Finally, we discuss the challenges and potential development of iris recognition. This review provides a comprehensive sight of the research of iris recognition based on deep learning.
... Recently, Convolutional Neural Networks (CNN) approach was introduced as one competitive approach iris recognition, [47]. The most recent works that have used the approach of CNN for iris recognition were [48]- [51]. ...
An iris recognition system for person identification is
developed with a new method for iris localization. For pupil
boundary detection, a method robust to the specular point
reflection problem is developed. It consists of morphological filter
and two-direction scanning methods. For limbic boundary
detection, Wildes method is modified by restricting the process of
Canny edge detector and Hough transform to a small Region-Of-
Interest (ROI) not exceeding 20% of the image size. For eyelid
detection, the method of Refine-Connect-Extend-Smooth (R-C-ES)
is used, which detect three possible cases (single eyelid, both
eyelids and free iris). For iris normalization, rubber-sheet model
transform is used and for iris coding Gabor filter is used. The
performance of the system is evaluated for the individual stages
and for the whole system using three different databases (CASIAV1.0,
CASIA-V4.0-Lamp and SDUMLA-HMT). The accuracy of
correct detection reached 99.9%-100% for pupil boundary and
99.6%-99.9% for limbic boundary detection. For eyelid detection;
the accuracy reached 93.2%-97.6% for upper eyelid, 95.3%-
99.15% for lower eyelid and 96.7%-96.92% for free iris (iris not
occluded by eyelids). The overall accuracy and the Equal Error
Rate (EER) of the system for CASIA-V1.0 database are 96.48%
and 1.76%, for CASIA-V4.0-Lamp, are 95.1% and 2.45%, and for
SDUMLA-HMT are 93.6% and 3.2%.
EFFECT OF SOLAR THERMAL RADIATION AND MAGNETIC FIELD ON THE FLOW OF CASSON FLUID
Abstract
In this paper, the behavior of the non-Newtonian fluid and heat transfer is considered in an
exponentially stretching surface in the occurrence of porous magnetic field, as it has vast
applications in the field of several industries. An explicit Finite difference method is applied
for the solution of governing equations. By considering governing equations of the
mathematical model as a platform non-linier differential equation have been reduced to
ordinary differential equations by using similarity transformations. BVP4C software
technique is used for finding the solutions and results are presented in the form of tables and
graphs for several equations. After simulation, it is found that the heat transfer rate decreases
with higher values of the magnetic field as well as the radiation. The temperature profile and
velocity profile of the Casson fluid flow is directly related to several parameters. Finally, it is
observed that several parameters such as Casson fluid parameter, radiation parameter, Prandtl
number, and Eckert number are stable at the point of convergence.
Iris Recognition Technology is a biometric method that takes an image of an eye pattern, converts the image into a binary template and then saves the data on a server for future matching. Iris cameras are used to learn the unique identity of an individual by analyzing unique random patterns that appear clearly inside the eye from a certain distance. It uses multiple techniques including optics, statistical inferences, pattern recognition and many more. Because the market is primarily driven by the increasing demand for security systems, some information about the market for this technology and future predictions has been presented in this paper.
