scholarly journals IRIS Recognition using Hough Transform

2019 ◽  
Vol 8 (9S3) ◽  
pp. 504-507
Keyword(s):  
Light Source ◽  
Hough Transform ◽  
Iris Recognition ◽  
Near Infrared ◽  
Hill Climbing ◽  
Iris Localization ◽  
Visible Wavelength ◽  
Area Of Interest ◽  
Iris Identification ◽  
Close Distance

In most iris identification systems, the complete image acquires constraints are understood. These Constrain include near-infrared (NIR) illumination to release the iris texture and close distance from the capturing device. In recent advances to different illumination technologies introduced in images captured in the environment. This environment includes a visible wavelength (VW) light source at-a-distance over the close distance from the capturing device. For accurate Iris identification at-a-distance, eye images require improvement of effective strategies, while setting the light source at a distance from the planar view of the iris. Effectively performing feature extraction technique for Near-Infrared and Visible wavelength images, that were collected in an uncontrolled stage. The identification of iris accuracy on the publicly available databases was then measured. This paper presents a preprocessing of Iris Recognition using Hough Transform (HT) for Iris Area of interest (AOI) and rubber-sheeting the model captured using linear stretching and rotation for normalization. The HT is used to filter and contrast stretch the iris regions from multispectral iris images. A basic purpose of this research is to envelop a design and implement IRIS-recognition at a distance (IAAD) by adopting a frequency and wavelength-based Hough transform for accurate feature selection [1][2]. The proposed method is described as follows: Initially, the input iris image will be subjected to pre-processing while extracting features with differences from local extrema and maxima conditions, using a regular shape filling Hough transform [3][4]. The iris localization and detection consists of a hill climbing segmentation approach that is based on geometric shape Hough measure. Proposed in comparison to the contemporary

scholarly journals Accurate Iris Localization Using Edge Map Generation and Adaptive Circular Hough Transform for Less Constrained Iris Images

2016 ◽  
Vol 6 (4) ◽  
pp. 1637 ◽  
Author(s):  
Vineet Kumar ◽  
Abhijit Asati ◽  
Anu Gupta
Keyword(s):  
Hough Transform ◽  
Near Infrared ◽  
Boundary Detection ◽  
Morphological Operations ◽  
Localization Algorithm ◽  
Iris Localization ◽  
Circular Hough Transform ◽  
Map Generation ◽  
Sobel Edge Detection ◽  
Binary Edge

This paper proposes an accurate iris localization algorithm for the iris images acquired under near infrared (NIR) illuminations and having noise due to eyelids, eyelashes, lighting reflections, non-uniform illumination, eyeglasses and eyebrow hair etc. The two main contributions in the paper are an edge map generation technique for pupil boundary detection and an adaptive circular Hough transform (CHT) algorithm for limbic boundary detection, which not only make the iris localization more accurate but faster also. The edge map for pupil boundary detection is generated on intersection (logical AND) of two binary edge maps obtained using thresholding, morphological operations and Sobel edge detection, which results in minimal false edges caused by the noise. The adaptive CHT algorithm for limbic boundary detection searches for a set of two arcs in an image instead of a full circle that counters iris-occlusions by the eyelids and eyelashes. The proposed CHT and adaptive CHT implementations for pupil and limbic boundary detection respectively use a two-dimensional accumulator array that reduces memory requirements. The proposed algorithm gives the accuracies of 99.7% and 99.38% for the challenging CASIA-Iris-Thousand (version 4.0) and CASIA-Iris-Lamp (version 3.0) databases respectively. The average time cost per image is 905 msec. The proposed algorithm is compared with the previous work and shows better results.

scholarly journals Second-Order Statistical Methods GLCM for Authentication Systems

2021 ◽  
Vol 17 (1) ◽  
pp. 1-6
Author(s):  
Mohammed Taha ◽  
Hanaa Ahmed
Keyword(s):  
Iris Recognition ◽  
Near Infrared ◽  
Color Image ◽  
Visible Spectrum ◽  
Second Order ◽  
Infrared Light ◽  
Identification System ◽  
Extraction Technology ◽  
Occurrence Matrix ◽  
Iris Identification

For many uses, biometric systems have gained considerable attention. Iris identification was One of the most powerful sophisticated biometrical techniques for effective and confident authentication. The current iris identification system offers accurate and reliable results based on near-infrared light (NIR) images when images are taken in a restricted area with fixed-distance user cooperation. However, for the color eye images obtained under visible wavelength (VW) without collaboration among the users, the efficiency of iris recognition degrades because of noise such as eye blurring images, eye lashing, occlusion, and reflection. This work aims to use the Gray-Level Co- occurrence Matrix (GLCM) to retrieve the iris's characteristics in both NIR iris images and visible spectrum. GLCM is second-order Statistical-Based Methods for Texture Analysis. The GLCM-based extraction technology was applied after the preprocessing method to extract the pure iris region's characteristics. The Energy, Entropy, Correlation, homogeneity, and Contrast collection of second-order statistical features are determined from the generated co-occurrence matrix, Stored as a vector for numerical features. This approach is used and evaluated on the CASIA v1and ITTD v1 databases as NIR iris image and UBIRIS v1 as a color image. The results showed a high accuracy rate (99.2 %) on CASIA v1, (99.4) on ITTD v1, and (87%) on UBIRIS v1 evaluated by comparing to the other methods

scholarly journals Structure of Iris Recognition technique

2019 ◽  
Vol 9 (1) ◽  
pp. 5200-5204
Keyword(s):  
Light Source ◽  
Hough Transform ◽  
Iris Recognition ◽  
Mirror Plane ◽  
Iris Image ◽  
The Earth ◽  
Human Iris ◽  
Recognition Technique

In many iris recognizable proof frameworks, the total image obtains requirements are understood. These imperatives incorporate close infrared (NIR) enlightenment to release the co-events of surface measures in the mirror plane of human iris, just as closeness in the output lines of a device. In ongoing advances to various light developments presented in images caught in the earth. This condition incorporates an obvious wavelength (VW) light source a good way off over the nearby good ways from the catching device. For precise Iris recognizable proof a ways off, eye images require improvement of successful systems, whereas the light source is situating good ways off after the planar perspective on the iris. Adequately acting a highpoint abstraction system aimed at Close Infrared too Obvious wavelength images, the images are composed unrestrained point. The recognizable proof of iris exactness on the freely accessible database remained estimated here uses Hough transform algorithm to caught utilizing straight extending and turn for standardization. for utilizing towards channel also differentiation stretches the iris areas from multispectral iris images. An essential motivation behind this examination is to encompass a structure and actualize IRIS-recognition a good ways off (IAAD) by embracing a recurrence then Hough Transform change intended for exact element choice [1][2]. Here proposed strategy is depicted as pursues: At first, the information iris image will be exposed in the direction of pre-handling though at the same time separating highpoints with contrasts from neighborhood extrema also highest conditions. [3][4].

Accurate Iris Localization Using Edge Map Generation and Adaptive Circular Hough Transform for Less Constrained Iris Images

2016 ◽  
Vol 6 (4) ◽  
pp. 1637
Author(s):  
Vineet Kumar ◽  
Abhijit Asati ◽  
Anu Gupta
Keyword(s):  
Hough Transform ◽  
Near Infrared ◽  
Boundary Detection ◽  
Morphological Operations ◽  
Localization Algorithm ◽  
Iris Localization ◽  
Circular Hough Transform ◽  
Map Generation ◽  
Sobel Edge Detection ◽  
Binary Edge

This paper proposes an accurate iris localization algorithm for the iris images acquired under near infrared (NIR) illuminations and having noise due to eyelids, eyelashes, lighting reflections, non-uniform illumination, eyeglasses and eyebrow hair etc. The two main contributions in the paper are an edge map generation technique for pupil boundary detection and an adaptive circular Hough transform (CHT) algorithm for limbic boundary detection, which not only make the iris localization more accurate but faster also. The edge map for pupil boundary detection is generated on intersection (logical AND) of two binary edge maps obtained using thresholding, morphological operations and Sobel edge detection, which results in minimal false edges caused by the noise. The adaptive CHT algorithm for limbic boundary detection searches for a set of two arcs in an image instead of a full circle that counters iris-occlusions by the eyelids and eyelashes. The proposed CHT and adaptive CHT implementations for pupil and limbic boundary detection respectively use a two-dimensional accumulator array that reduces memory requirements. The proposed algorithm gives the accuracies of 99.7% and 99.38% for the challenging CASIA-Iris-Thousand (version 4.0) and CASIA-Iris-Lamp (version 3.0) databases respectively. The average time cost per image is 905 msec. The proposed algorithm is compared with the previous work and shows better results.

Electrically Driven Near-Infrared Broadband Light Source with Gaussian-Like Spectral Shape Based on Multiple InAs Quantum Dots

2016 ◽  
Vol E99.C (3) ◽  
pp. 381-384 ◽  
Author(s):  
Takuma YASUDA ◽  
Nobuhiko OZAKI ◽  
Hiroshi SHIBATA ◽  
Shunsuke OHKOUCHI ◽  
Naoki IKEDA ◽  
...  
Keyword(s):  
Quantum Dots ◽  
Light Source ◽  
Near Infrared ◽  
Spectral Shape ◽  
Inas Quantum Dots ◽  
Broadband Light Source

An Infrared Microscope for Use on a Focused Ion Beam for Circuit Edit and Backside Edit Applications

2015 ◽  
Author(s):  
Alexander Richards ◽  
Matthew Weschler ◽  
Michael Durller
Keyword(s):  
Focused Ion Beam ◽  
Near Infrared ◽  
Ion Beam ◽  
Visible Spectrum ◽  
Camera System ◽  
Buried Structures ◽  
Ir Camera ◽  
Area Of Interest ◽  
Near Ultraviolet ◽  
Infrared Microscope

Abstract To help solve the navigational problem, i.e., being able to successfully locate a circuit for probing or editing without destroying chip functionality, a near-infrared (NIR), near-ultraviolet (NUV), and visible spectrum camera system was developed that attaches to most focused ion beam (FIB) or scanning electron microscope vacuum chambers. This paper reviews the details of the design and implementation of the NIR/NUV camera system, as instantiated upon the FEI FIB 200, with a particular focus on its use for the visualization of buried structures, and also for non-destructive real time area of interest location and end point detection. It specifically considers the use of the micro-optical camera system for its benefit in assisting with frontside and backside circuit edit, as well as other typical FIB milling activities. The quality of the image obtained by the IR camera rivals or exceeds traditional optical based imaging microscopy techniques.

Ab Initio Two-sites Occupancy and Broadband Near-Infrared Emission of Cr3+ in Li2MgZrO4

2021 ◽  
Author(s):  
Xue Zhou ◽  
Jinmeng Xiang ◽  
Jiming Zheng ◽  
Xiaoqi Zhao ◽  
Hao Suo ◽  
...  
Keyword(s):  
Plant Growth ◽  
Ab Initio ◽  
Light Source ◽  
Near Infrared ◽  
Broad Band ◽  
Infrared Emission ◽  
Night Vision ◽  
Light Emitting ◽  
Non Destructive ◽  
Near Infrared Emission

Near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) light source have great potential in non-destructive detection, promoting plant growth and night vision applications, while the discovery of a broad-band NIR phosphor still...

scholarly journals Photothermal Therapy Using Gold Nanorods and Near-Infrared Light in a Murine Melanoma Model Increases Survival and Decreases Tumor Volume

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Mary K. Popp ◽  
Imane Oubou ◽  
Colin Shepherd ◽  
Zachary Nager ◽  
Courtney Anderson ◽  
...  
Keyword(s):  
Light Source ◽  
Gold Nanorods ◽  
Photothermal Therapy ◽  
Near Infrared ◽  
Tumor Volume ◽  
Infrared Light ◽  
Led Light ◽  
Murine Melanoma ◽  
Nir Light ◽  
Melanoma Model

Photothermal therapy (PTT) treatments have shown strong potential in treating tumors through their ability to target destructive heat preferentially to tumor regions. In this paper we demonstrate that PTT in a murine melanoma model using gold nanorods (GNRs) and near-infrared (NIR) light decreases tumor volume and increases animal survival to an extent that is comparable to the current generation of melanoma drugs. GNRs, in particular, have shown a strong ability to reach ablative temperatures quickly in tumors when exposed to NIR light. The current research tests the efficacy of GNRs PTT in a difficult and fast growing murine melanoma model using a NIR light-emitting diode (LED) light source. LED light sources in the NIR spectrum could provide a safer and more practical approach to photothermal therapy than lasers. We also show that the LED light source can effectively and quickly heatin vitroandin vivomodels to ablative temperatures when combined with GNRs. We anticipate that this approach could have significant implications for human cancer therapy.

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