Contact Lens Detection for Security (original) (raw)
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An Efficient Approach for Textured Contact Lenses Detection in Iris Recognition
International Journal of Innovative Technology and Research, 2016
The effective implementation associated with a product is largely based on its reliability,authenticity and the quantity of secrecy it offers.In the current high techno world where privacy and security are the worries of prime importance,the important systems must employ techniques to do this. Our project is simply a small step towards this.The iris based system can deal with lots of individual biological versions but still supply the identification system with a lot more precision and reliability. Within this project we've developed a system that involves recognition of the person using IRIS like a biometric parameter.We've first segmented the pupil and iris structure in the original eye image.Whenever we have normalised it to construct an element vector which characterizes each iris clearly.This selection vector will be employed for matching among various templates and identifies the person. The job provided within this project is principally targeted at supplying a recognition system to be able to verify the distinctiveness of human iris as well as its performance like a biometric.The paper has implementation of calculations on CASIA database.The different outcomes of different implementations as well as their accuracies happen to be examined within this paper. Overall within this paper,a truthful effort in recommending a competent system for implementation from the human identification system according to iris recognition and powerful recognition of textured contact contacts in iris recognition of images. This project presents an Iris recognition system, that was examined on CASIA iris image database, to be able to verify the stated performance of iris recognition technology.
Contact Lens Classification by Using Segmented Lens Boundary Features
Indonesian Journal of Electrical Engineering and Computer Science, 2018
Recent studies have shown that the wearing of soft lens may lead to performance degradation with the increase of false reject rate. However, detecting the presence of soft lens is a non-trivial task as its texture that almost indiscernible. In this work, we proposed a classification method to identify the existence of soft lens in iris image. Our proposed method starts with segmenting the lens boundary on top of the sclera region. Then, the segmented boundary is used as features and extracted by local descriptors. These features are then trained and classified using Support Vector Machines. This method was tested on Notre Dame Cosmetic Contact Lens 2013 database. Experiment showed that the proposed method performed better than state of the art methods.
Feature extraction for IRIS recognition
Communications in Computer and Information Science, 2009
Iris templates can be matched using various matching techniques; each approach to iris recognition has several aspects being taken into consideration. One of the most important aspect being the presence of a lens in the users eye. The biometric templates, including iris and users attributes which are produced by using different recognition techniques can be matched through the Iris-templates can be replicated. From this we conclude that, without a thorough security analysis, iris templates cannot be assumed safe and secure. In this paper, we are going to discuss about the presence of a contact lens, particularly a colored lens, and the challenges we face as it alters the natural iris patterns. In this paper we will use a feature extraction method to remove the effect of colored contact lenses and make it more secure. This has proven to be very efficient and also less space consuming.
IJRCAR, 2014
Iris is one of the most promising biometric modalities, and is in usual use in enormously large-scale applications. The presences of a contact lens, mainly a textured cosmetic lens, create a challenge to iris recognition as it obfuscates the natural iris patterns. Earlier work used novel lens detection algorithm with Modified Local Binary Pattern analysis (MLBP) features to produce feature values. Two databases, namely, the IIIT-D Iris Contact Lens database and the ND-Contact Lens database, are organized to analyze the variations caused due to contact lenses. However lower accuracy is obtained for various pairs of gallery probe pairs due to less accurate lens detection algorithm. To deal this problem, the present work proposes PSVM Based Lens detection method using two additional features namely iris edge sharpness and Iris-Texton features for characterizing visual primitives of Iris textures for textured and soft contact lens based iris. The problem of lens detection in an iris image is approached as a three class classification problem: no lens, soft lens, and textured lens. This classification is efficiently done by using Proximal Support Vector Machine Classifier. Proximal SVM classifier has comparable test set correctness to that of standard SVM classifiers, but with considerably faster computational time that can be an order of magnitude faster. Experimental result of proposed system provides better result when compared with existing system.
Iris and user attributes based recognition system by.pdf
The exploratory results express the biometric including iris and user attributes constructed by various recognition methods can be parallel through the central rays in their convex polyhedral cones. It is to prevent by a method enlarged from iris templates can be fragmented into various segments. The experimental results also brings out the fact that convex polyhedral cone templates cannot be secured without a thorough security. This paper manages how the part of cosmetic lens is served as a challenge to iris recognition as it obscures. The natural iris design manufactures have many types and colours of lenses. This experiment is done to analyze the effect of these parameters on iris recognition. Diagnosing the presence of a contact lens is the first step to improve the ease of use and unwavering quality of iris acknowledgment for contact lens wearers. The success of iris templates depends on its computational advantages high matching speed for large scale identification and automatic threshold adjustment based on image quality. Many terms modified from iris templates were propounded for iris and user attributes based recognition.
Image Processing on Eye Image Using SURFFeature Extraction
International Journal of Innovative Research in Computer and Communication Engineering, 2015
Mobile cloud computing (MCC) is an integration of the concept of cloud computing and mobile computing. When user is able to access cloud services through mobile phone on the basis of pay as per the use then we can see there the use of MCC. As users store their data in the cloud security is an important issue. To overcome this issue the biometric identification method is proposed where eye image is used as biometric input. The image goes through some image processing steps required to extract its features. This paper proposed an algorithm required for image processing.
Soft Lens Detection in Iris Image using Lens Boundary Analysis and Pattern Recognition Approach
International Journal of Advanced Trends in Computer Science and Engineering , 2021
Recent studies have demonstrated that the soft lens wearing during iris recognition has indicated the increase of false reject rate. It denies the strong belief that the soft lens wearing will cause no performance degradation. Therefore, it is a necessity for an iris recognition system to be able to detect the presence of soft lens prior to iris recognition. As a first step towards soft lens detection, this study proposed a method for segmenting the soft lens boundary in iris images. However, segmenting the soft lens boundary is a very challenging task due to its marginal contrast. Besides, the flash lighting effect during the iris image enrolment has caused the image to suffer from inconsistent illumination. In addition, the visibility condition of the soft lens boundary may be discerned as a bright or dark ridge as a result of the flash lighting. Three image enhancement techniques were therefore proposed in order to enhance the contrast of the soft lens boundary and to provide an even distribution of intensities across the image. A method called summed-histogram has been incorporated as a solution to classify the visibility condition of the soft lens boundary automatically. The visibility condition of the ridge is used to determine the directional directive magnitude by the ridge detection algorithm. The proposed method was evaluated with Notre Dame Contact Lens Detection 2013 database. Results showed that the proposed method has successfully segment the soft lens boundary with an accuracy of over 92%.
Sift Algorithm for Iris Feature Extraction
Global journal of computer science and technology, 2014
Iris recognition is proving to be one of the most reliable biometric traits for personal identification. In fact, iris patterns have stable, invariant and distinctive features for personal identification. Reliable authorization and authentication are becoming necessary for many everyday applications. Iris recognition has been paid more attention due to its high reliability in personal identification. But iris feature extraction is easily affected by some practical factors, such as inaccurate localization, occlusion, and nonlinear elastic deformation. The objective of the study and proposed work is to adapt the increasing usage of biometric systems which can reduce the iris preprocessing and describe iris local properties effectively and have encouraging iris recognition performance. This work presents an efficient algorithm of iris feature extraction based on modified scale invariant feature transform algorithm (SIFT) .
Ocular biometrics: automatic feature extraction from eye images
2011
We presents a general framework for image processing of eye images with a particular view on feature extraction. In eye imaging the process of the diagnosis and feature extraction is one complete system and extracting features from eye images can be used to automated interpretation of the images. We consider for human recognition based on the retinal and the conjunctival vasculature.
Iris Features Extraction and Recognition based on the Scale Invariant Feature Transform (SIFT)
Webology, 2022
Iris Biometric authentication is considered to be one of the most dependable biometric characteristics for identifying persons. In actuality, iris patterns have invariant, stable, and distinguishing properties for personal identification. Due to its excellent dependability in personal identification, iris recognition has received more attention. Current iris recognition methods give good results especially when NIR and specific capture conditions are used in collaboration with the user. On the other hand, values related to images captured using VW are affected by noise such as blurry images, eye skin, occlusion, and reflection, which negatively affects the overall performance of the recognition systems. In both NIR and visible spectrum iris images, this article presents an effective iris feature extraction strategy based on the scale-invariant feature transform algorithm (SIFT). The proposed method was tested on different databases such as CASIA v1 and ITTD v1, as NIR images, as wel...