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Automatic Text Detection Using Morphological Operations and Inpainting
KHYATI VAGHELA, NARENDRA PATEL
International Journal of Innovative Research in Science, Engineering and Technology , 2013,
Abstract: Image inpainting is the process of restoring the lost or damaged regions or modifying the image contents imperceptibly. It refers to the process of filling-in missing data in a designated region of the visual input. In this paper, the technique presented is for detection and removal of text from images. The system detects text using morphological operations, connected component labelling and a set of selection criteria which helps to filter out non text regions. So, the resultant image is the image with only texts. Text Inpainting is done in two steps. The first step detects the text region automatically, without user interaction and in the second step; the text is removed from the image using exemplar based Inpainting algorithm.
Detection and Estimation of Iris Centre  [PDF]
Anirban Dasgupta,Aurobinda Routray,Sai Nataraj Mallavollu
Computer Science , 2015,
Abstract: Detection of iris center is an active area of research in the field of computer vision and human-machine interaction systems. The major issues involved in the detection of iris involves glint on the corneal region, occlusion of the iris by eye-lids, occlusions due to eye gaze, high speed of processing etc. This paper presents an algorithm for detecting and estimating the iris center thereby addressing some of these issues.
Implementation of the Hough Transform for Iris Detection and Segmentation  [PDF]
Francisco Javier Paulín-Martínez, Alberto Lara-Guevara, Rosa María Romero-González, Hugo Jiménez-Hernández
Advances in Molecular Imaging (AMI) , 2019, DOI: 10.4236/ami.2019.91002
Abstract: The iris is used as a reference for the study of unique biometric marks in people. The analysis of how to extract the iris characteristic information represents a fundamental challenge in image analysis, due to the implications it presents: detection of relevant information, data coding schemes, etc. For this reason, in the search for extraction of useful and characteristic information, approximations have been proposed for its analysis. In this article, it is presented a scheme to extract the relevant information based on the Hough transform. This transform helps to find primitive geometries in the irises, which are used to characterize each one of these. The results of the implementation of the algorithm of the Hough transform applied to the location and segmentation of the iris by means of its circumference are presented in the paper. Two public databases of iris images were used: UBIRIS V2 and CASIA-IrisV4, which were acquired under the same conditions and controlled environments. In the pre-processing stage the edges are found from the noise elimination in the image through the Canny detector. Subsequently, to the images of the detected edges, the Hough transform is applied to the disposition of the geometries detected.
Localization of License Plate Using Morphological Operations  [PDF]
V. Karthikeyan,V. J. Vijayalakshmi
Computer Science , 2014,
Abstract: It is believed that there are currently millions of vehicles on the roads worldwide. The over speed of vehicles,theft of vehicles, disobeying traffic rules in public, an unauthorized person entering the restricted area are keep on increasing. In order restrict against these criminal activities, we need an automatic public security system. Each vehicle has their own Vehicle Identification Number (VIN) as their primary identifier. The VIN is actually a License Number which states a legal license to participate in the public traffic. The proposed paper is to identify the vehicle with the help of vehicles License Plate (LP).LPRS is one the most important part of the Intelligent Transportation System (ITS) to locate the LP. In this paper certain existing algorithm drawbacks are overcome by the proposed morphological operations for LPRS. Morphological operation is chosen due to its higher efficiency, noise filter capacity, accuracy, exact localization of LP and speed.
Iris Recognition System using canny edge detection for Biometric Identification
Bhawna Chouhan,Dr. (Mrs.) Shailja Shukla
International Journal of Engineering Science and Technology , 2011,
Abstract: biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. Especially it focuses on image segmentation and feature extraction for iris recognition process. The performance of iris recognition system highly depends on edge detection. The Canny Edge Detector is one of the most commonly used image processing tools, detecting edges in a very robust manner. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. This paper presents a straightforward approach for segmenting the iris patterns. The used method determines an automated global threshold and the pupil center. Experiments are performed using iris images obtained from CASIA database (Institute of Automation, Chinese Academy of Sciences) and Matlab application for its easy and efficient tools in image manipulation.
Deep Representations for Iris, Face, and Fingerprint Spoofing Detection  [PDF]
David Menotti,Giovani Chiachia,Allan Pinto,William Robson Schwartz,Helio Pedrini,Alexandre Xavier Falcao,Anderson Rocha
Computer Science , 2014,
Abstract: Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or "spoofed") and, despite the recent advances in spoofing detection, current solutions often rely on domain knowledge, specific biometric reading systems, and attack types. We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches. The first approach consists of learning suitable convolutional network architectures for each domain, while the second approach focuses on learning the weights of the network via back-propagation. We consider nine biometric spoofing benchmarks --- each one containing real and fake samples of a given biometric modality and attack type --- and learn deep representations for each benchmark by combining and contrasting the two learning approaches. This strategy not only provides better comprehension of how these approaches interplay, but also creates systems that exceed the best known results in eight out of the nine benchmarks. The results strongly indicate that spoofing detection systems based on convolutional networks can be robust to attacks already known and possibly adapted, with little effort, to image-based attacks that are yet to come.
A new Morphological Approach for Noise Removal cum Edge Detection  [PDF]
M. Rama Bai,V. Venkata Krishna,J. SreeDevi
International Journal of Computer Science Issues , 2010,
Abstract: Edge detection is an important aspect in image processing. When a noisy image is presented for edge detection, the noise creates problem in the process of edge detection using conventional methods. One of the disadvantages of the conventional methods is that the noise is not removed automatically. The present paper proposes a novel approach for noise removal cum edge detection for both gray scale and binary images using morphological operations. Two images consisting of noise are processed and the effectiveness of the proposed approach is experimentally demonstrated. The results demonstrate that the proposed filter cum edge detector approach overcomes the deficiency of conventional methods and efficiently removes the noise and detects the edges.
Dissecting the morphological and spectroscopic properties of galaxies in the local Universe: I. Elliptical galaxies  [PDF]
J. A. L. Aguerri,M. Huertas-Company,J. Sánchez Almeida,C. Munoz-Tunon
Physics , 2012, DOI: 10.1051/0004-6361/201117632
Abstract: We revisit the scaling relations and star-forming histories of local elliptical galaxies using a novel selection method applied to the Sloan Digital Sky Survey DR7. We combine two probability-based automated spectroscopic and morphological classifications of about 600000 galaxies with z<0.25 to isolate true elliptical galaxies. Our sample selection method does not introduce artificial cuts in the parameters describing the galaxy but instead it associates to every object a weight measuring the probability of being in a given spectro-morphological class. Thus the sample minimizes the selection biases. We show that morphologically defined ellipticals are basically distributed in 3 spectral classes, which dominate at different stellar masses. The bulk of the population (about 50%) is formed by a well defined class of galaxies with old stellar populations that formed their stars at very early epochs in a short episode of star formation. They dominate the scaling relations of elliptical galaxies known from previous works and represent the canonical elliptical class. At the low mass end, we find a population of slightly larger ellipticals, with smaller velocity dispersions at fixed stellar mass, which seem to have experienced a more recent episode of star formation probably triggered by gas-rich minor mergers. The high mass end tends to be dominated by a third spectral class, slightly more metal rich and with more efficient stellar formation than the reference class. This third class contributes to the curvature of the mass-size relation at high masses reported in previous works. Our method is therefore able to isolate typical spectra of elliptical galaxies following different evolutive pathways.
Integrate Liveness Detection with Iris Verification to Construct Support Biometric System  [PDF]
Hanaa Mohsin Ahmad, Bushra Jabbar Abdulkareem
Journal of Computer and Communications (JCC) , 2016, DOI: 10.4236/jcc.2016.41003
Abstract: The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks to the biometric verification system to ensure the security of these systems against spoof attacks and reduce this risk, by using another module that is added to the biometric verification system called the “liveness detection” which uses different anatomical properties to distinguish between real and fake traits. Thus, the robustness of the system against direct attacks can be improved through increasing the security level offered to the final user. This paper is an attempt to construct support biometric security system to protect the iris biometric verification system from spoof attacks, through integrating the iris verification system with addition module called liveness detection which composed of two sub-modules (static and dynamic). A test has been performed, for iris verification phase performed on two types of database (MMU DB) for 180 samples and (CASIA DB) for 90 samples, and gave accuracy (99.44%) with FAR of (0.0277) and FRR (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB.
From Bipolar to Elliptical: Morphological Changes in the Temporal Evolution of PN  [PDF]
Martin Huarte Espinosa,Adam Frank,Bruce Balick,Orsola De Marco,Joel H. Kastner,Raghvendra Sahai,Eric G. Blackman
Physics , 2010,
Abstract: Proto-planetary nebulae (pPN) and planetary nebulae (PN) seem to be formed by interacting winds from asymptotic giant branch (AGB) stars. The observational issue that most pPN are bipolar but most older PN are elliptical is addressed. We present 2.5D hydrodynamical numerical simulations of episodic cooling interacting winds to investigate the long term evolution of PN morphologies. We track wind acceleration, decrease in mass-loss and episodic change in wind geometry from spherical (AGB) to collimated (pPN) and back to spherical again (PN). This outflow sequence is found to produce realistic PN dynamics and morphological histories. Effects from different AGB distributions and jet duty cycles are also investigated.
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