Search results for: Iris segmentation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 365

Search results for: Iris segmentation

365 An Efficient Segmentation Method Based on Local Entropy Characteristics of Iris Biometrics

Authors: Ali Shojaee Bakhtiari, Ali Asghar Beheshti Shirazi, Amir Sepasi Zahmati

Abstract:

An efficient iris segmentation method based on analyzing the local entropy characteristic of the iris image, is proposed in this paper and the strength and weaknesses of the method are analyzed for practical purposes. The method shows special strength in providing designers with an adequate degree of freedom in choosing the proper sections of the iris for their application purposes.

Keywords: Iris segmentation, entropy, biocryptosystem, biometric identification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1411
364 A Method for Iris Recognition Based on 1D Coiflet Wavelet

Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa

Abstract:

There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.

Keywords: Biometric, iris recognition, wavelet transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1884
363 New Corneal Reflection Removal Method Used In Iris Recognition System

Authors: Walid Aydi, Nouri Masmoudi, Lotfi Kamoun

Abstract:

Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address the corneal reflection, a novel reflection removal method is proposed in this paper. Comparative experiments of two existing methods for reflection removal method are evaluated on CASIA iris image databases V3. The experimental results reveal that the proposed algorithm provides higher performance in reflection removal.

Keywords: iris, pupil, specular highlights, reflection removal

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3187
362 Improved Feature Processing for Iris Biometric Authentication System

Authors: Somnath Dey, Debasis Samanta

Abstract:

Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature processing is an important task. In feature processing, we extract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature extraction and feature matching process. We apply Daubechies D4 wavelet with 4 levels to extract features from iris images. These features are encoded with 2 bits by quantizing into 4 quantization levels. With our proposed approach it is possible to represent an iris template with only 304 bits, whereas existing approaches require as many as 1024 bits. In addition, we assign different weights to different iris region to compare two iris templates which significantly increases the accuracy. Further, we match the iris template based on a weighted similarity measure. Experimental results on several iris databases substantiate the efficacy of our approach.

Keywords: Iris recognition, biometric, feature processing, patternrecognition, pattern matching.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2121
361 Efficient Iris Recognition Method for Human Identification

Authors: A. Basit, M. Y. Javed, M. A. Anjum

Abstract:

In this paper, an efficient method for personal identification based on the pattern of human iris is proposed. It is composed of image acquisition, image preprocessing to make a flat iris then it is converted into eigeniris and decision is carried out using only reduction of iris in one dimension. By comparing the eigenirises it is determined whether two irises are similar. The results show that proposed method is quite effective.

Keywords: Biometrics, Canny Operator, Eigeniris, Iris Recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1521
360 A Novel Approach to Iris Localization for Iris Biometric Processing

Authors: Somnath Dey, Debasis Samanta

Abstract:

Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.

Keywords: Iris recognition, iris localization, biometrics, image processing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3161
359 Iris Localization using Circle and Fuzzy Circle Detection Method

Authors: Marzieh. Savoj, S. Amirhassan. Monadjemi

Abstract:

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we consider Daugman iris localization method as a standard method, propose a new method in this field and then analyze and compare the results of them on a standard set of iris images. The proposed method is based on the detection of circular edge of iris, and improved by fuzzy circles and surface energy difference contexts. Implementation of this method is so easy and compared to the other methods, have a rather high accuracy and speed. Test results show that the accuracy of our proposed method is about Daugman method and computation speed of it is 10 times faster.

Keywords: Convolution, Edge detector filter, Fuzzy circle, Identification

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2017
358 Efficient Feature Fusion for Noise Iris in Unconstrained Environment

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: Image fusion, iris recognition, local binary pattern, wavelet.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2193
357 Size-Reduction Strategies for Iris Codes

Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple subsampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two-stage identification approach, using small-sized iris code templates in a pre-selection stage, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: Iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1766
356 Performance Evaluation of Iris Region Detection and Localization for Biometric Identification System

Authors: Chit Su Htwe, Win Htay

Abstract:

The iris recognition technology is the most accurate, fast and less invasive one compared to other biometric techniques using for example fingerprints, face, retina, hand geometry, voice or signature patterns. The system developed in this study has the potential to play a key role in areas of high-risk security and can enable organizations with means allowing only to the authorized personnel a fast and secure way to gain access to such areas. The paper aim is to perform the iris region detection and iris inner and outer boundaries localization. The system was implemented on windows platform using Visual C# programming language. It is easy and efficient tool for image processing to get great performance accuracy. In particular, the system includes two main parts. The first is to preprocess the iris images by using Canny edge detection methods, segments the iris region from the rest of the image and determine the location of the iris boundaries by applying Hough transform. The proposed system tested on 756 iris images from 60 eyes of CASIA iris database images.

Keywords: Canny, C#, hough transform, image preprocessing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2067
355 A Weighted Approach to Unconstrained Iris Recognition

Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1917
354 Reducing the False Rejection Rate of Iris Recognition Using Textural and Topological Features

Authors: M. Vatsa, R. Singh, A. Noore

Abstract:

This paper presents a novel iris recognition system using 1D log polar Gabor wavelet and Euler numbers. 1D log polar Gabor wavelet is used to extract the textural features, and Euler numbers are used to extract topological features of the iris. The proposed decision strategy uses these features to authenticate an individual-s identity while maintaining a low false rejection rate. The algorithm was tested on CASIA iris image database and found to perform better than existing approaches with an overall accuracy of 99.93%.

Keywords: Iris recognition, textural features, topological features.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1917
353 A Comparative Study of Image Segmentation Algorithms

Authors: Mehdi Hosseinzadeh, Parisa Khoshvaght

Abstract:

In some applications, such as image recognition or compression, segmentation refers to the process of partitioning a digital image into multiple segments. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. Image segmentation is to classify or cluster an image into several parts (regions) according to the feature of image, for example, the pixel value or the frequency response. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image. Several image segmentation algorithms were proposed to segment an image before recognition or compression. Up to now, many image segmentation algorithms exist and be extensively applied in science and daily life. According to their segmentation method, we can approximately categorize them into region-based segmentation, data clustering, and edge-base segmentation. In this paper, we give a study of several popular image segmentation algorithms that are available.

Keywords: Image Segmentation, hierarchical segmentation, partitional segmentation, density estimation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2892
352 A Review on Image Segmentation Techniques and Performance Measures

Authors: David Libouga Li Gwet, Marius Otesteanu, Ideal Oscar Libouga, Laurent Bitjoka, Gheorghe D. Popa

Abstract:

Image segmentation is a method to extract regions of interest from an image. It remains a fundamental problem in computer vision. The increasing diversity and the complexity of segmentation algorithms have led us firstly, to make a review and classify segmentation techniques, secondly to identify the most used measures of segmentation performance and thirdly, discuss deeply on segmentation philosophy in order to help the choice of adequate segmentation techniques for some applications. To justify the relevance of our analysis, recent algorithms of segmentation are presented through the proposed classification.

Keywords: Classification, image segmentation, measures of performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2025
351 Multi-algorithmic Iris Authentication System

Authors: Hunny Mehrotra, Banshidhar Majhi, Phalguni Gupta

Abstract:

The paper proposes a novel technique for iris recognition using texture and phase features. Texture features are extracted on the normalized iris strip using Haar Wavelet while phase features are obtained using LOG Gabor Wavelet. The matching scores generated from individual modules are combined using sum of score technique. The system is tested on database obtained from Bath University and Indian Institute of Technology Kanpur and is giving an accuracy of 95.62% and 97.66% respectively. The FAR and FRR of the combined system is also reduced comparatively.

Keywords: Fusion, Haar Wavelet, Iris, LOG Gabor Wavelet, Phase, Texture.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1675
350 Lung Segmentation Algorithm for CAD System in CTA Images

Authors: H. Özkan, O. Osman, S. Şahin, M. M. Atasoy, H. Barutca, A. F. Boz, A. Olsun

Abstract:

In this study, we present a new and fast algorithm for lung segmentation using CTA images. This process is quite important especially at lung vessel segmentation, detection of pulmonary emboly, finding nodules or segmentation of airways. Applied method has been carried out at four steps. At first step, images have been applied optimal threshold. At the second one, the subsegment vessels, which have a place in lung region and which are in small dimension, have been removed. At the third one, identifying and segmentation of lungs and airway edges have been carried out. Lastly, by throwing away the airway, lung segmentation has been presented.

Keywords: Lung segmentation, computed tomography angiography, computer-aided diagnostic system

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1985
349 A Comparative Study of Image Segmentation using Edge-Based Approach

Authors: Rajiv Kumar, Arthanariee A. M.

Abstract:

Image segmentation is the process to segment a given image into several parts so that each of these parts present in the image can be further analyzed. There are numerous techniques of image segmentation available in literature. In this paper, authors have been analyzed the edge-based approach for image segmentation. They have been implemented the different edge operators like Prewitt, Sobel, LoG, and Canny on the basis of their threshold parameter. The results of these operators have been shown for various images.

Keywords: Edge Operator, Edge-based Segmentation, Image Segmentation, Matlab 10.4.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3582
348 An Efficient Biometric Cryptosystem using Autocorrelators

Authors: R. Bremananth, A. Chitra

Abstract:

Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Autocorrelators, biometrics cryptography, irispatterns, wavelets.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1509
347 Fast Document Segmentation Using Contourand X-Y Cut Technique

Authors: Boontee Kruatrachue, Narongchai Moongfangklang, Kritawan Siriboon

Abstract:

This paper describes fast and efficient method for page segmentation of document containing nonrectangular block. The segmentation is based on edge following algorithm using small window of 16 by 32 pixels. This segmentation is very fast since only border pixels of paragraph are used without scanning the whole page. Still, the segmentation may contain error if the space between them is smaller than the window used in edge following. Consequently, this paper reduce this error by first identify the missed segmentation point using direction information in edge following then, using X-Y cut at the missed segmentation point to separate the connected columns. The advantage of the proposed method is the fast identification of missed segmentation point. This methodology is faster with fewer overheads than other algorithms that need to access much more pixel of a document.

Keywords: Contour Direction Technique, Missed SegmentationPoints, Page Segmentation, Recursive X-Y Cut Technique

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2751
346 Effects of Reversible Watermarking on Iris Recognition Performance

Authors: Andrew Lock, Alastair Allen

Abstract:

Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance ofinvestigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: Biometrics, iris recognition, reversible watermarking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2370
345 A Robust Eyelashes and Eyelid Detection in Transformation Invariant Iris Recognition: In Application with LRC Security System

Authors: R. Bremananth

Abstract:

Biometric authentication is an essential task for any kind of real-life applications. In this paper, we contribute two primary paradigms to Iris recognition such as Robust Eyelash Detection (RED) using pathway kernels and hair curve fitting synthesized model. Based on these two paradigms, rotation invariant iris recognition is enhanced. In addition, the presented framework is tested with real-life iris data to provide the authentication for LRC (Learning Resource Center) users. Recognition performance is significantly improved based on the contributed schemes by evaluating real-life irises. Furthermore, the framework has been implemented using Java programming language. Experiments are performed based on 1250 diverse subjects in different angles of variations on the authentication process. The results revealed that the methodology can deploy in the process on LRC management system and other security required applications.

Keywords: Authentication, biometric, eye lashes detection, iris scanning, LRC security, secure access.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1011
344 Iris Recognition Based On the Low Order Norms of Gradient Components

Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: Iris recognition, contrast stretching, gradient features, texture features, Euclidean metric.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1941
343 Application of Biometrics to Obtain High Entropy Cryptographic Keys

Authors: Sanjay Kanade, Danielle Camara, Dijana Petrovska-Delacretaz, Bernadette Dorizzi

Abstract:

In this paper, a two factor scheme is proposed to generate cryptographic keys directly from biometric data, which unlike passwords, are strongly bound to the user. Hash value of the reference iris code is used as a cryptographic key and its length depends only on the hash function, being independent of any other parameter. The entropy of such keys is 94 bits, which is much higher than any other comparable system. The most important and distinct feature of this scheme is that it regenerates the reference iris code by providing a genuine iris sample and the correct user password. Since iris codes obtained from two images of the same eye are not exactly the same, error correcting codes (Hadamard code and Reed-Solomon code) are used to deal with the variability. The scheme proposed here can be used to provide keys for a cryptographic system and/or for user authentication. The performance of this system is evaluated on two publicly available databases for iris biometrics namely CBS and ICE databases. The operating point of the system (values of False Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set by properly selecting the error correction capacity (ts) of the Reed- Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096% and FRR is 0.76%.

Keywords:

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2067
342 A Comparative Study of Medical Image Segmentation Methods for Tumor Detection

Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

Abstract:

Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: Features extraction, image segmentation, medical images, tumour detection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 547
341 Implementation of a Multimodal Biometrics Recognition System with Combined Palm Print and Iris Features

Authors: Rabab M. Ramadan, Elaraby A. Elgallad

Abstract:

With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: Iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, scale invariant feature transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 850
340 Recognition-based Segmentation in Persian Character Recognition

Authors: Mohsen Zand, Ahmadreza Naghsh Nilchi, S. Amirhassan Monadjemi

Abstract:

Optical character recognition of cursive scripts presents a number of challenging problems in both segmentation and recognition processes in different languages, including Persian. In order to overcome these problems, we use a newly developed Persian word segmentation method and a recognition-based segmentation technique to overcome its segmentation problems. This method is robust as well as flexible. It also increases the system-s tolerances to font variations. The implementation results of this method on a comprehensive database show a high degree of accuracy which meets the requirements for commercial use. Extended with a suitable pre and post-processing, the method offers a simple and fast framework to develop a full OCR system.

Keywords: OCR, Persian, Recognition, Segmentation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1813
339 3D Anisotropic Diffusion for Liver Segmentation

Authors: Wan Nural Jawahir Wan Yussof, Hans Burkhardt

Abstract:

Liver segmentation is the first significant process for liver diagnosis of the Computed Tomography. It segments the liver structure from other abdominal organs. Sophisticated filtering techniques are indispensable for a proper segmentation. In this paper, we employ a 3D anisotropic diffusion as a preprocessing step. While removing image noise, this technique preserve the significant parts of the image, typically edges, lines or other details that are important for the interpretation of the image. The segmentation task is done by using thresholding with automatic threshold values selection and finally the false liver region is eliminated using 3D connected component. The result shows that by employing the 3D anisotropic filtering, better liver segmentation results could be achieved eventhough simple segmentation technique is used.

Keywords: 3D Anisotropic Diffusion, non-linear filtering, CT Liver.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1570
338 Image Segmentation Based on Graph Theoretical Approach to Improve the Quality of Image Segmentation

Authors: Deepthi Narayan, Srikanta Murthy K., G. Hemantha Kumar

Abstract:

Graph based image segmentation techniques are considered to be one of the most efficient segmentation techniques which are mainly used as time & space efficient methods for real time applications. How ever, there is need to focus on improving the quality of segmented images obtained from the earlier graph based methods. This paper proposes an improvement to the graph based image segmentation methods already described in the literature. We contribute to the existing method by proposing the use of a weighted Euclidean distance to calculate the edge weight which is the key element in building the graph. We also propose a slight modification of the segmentation method already described in the literature, which results in selection of more prominent edges in the graph. The experimental results show the improvement in the segmentation quality as compared to the methods that already exist, with a slight compromise in efficiency.

Keywords: Graph based image segmentation, threshold, Weighted Euclidean distance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1540
337 Hippocampus Segmentation using a Local Prior Model on its Boundary

Authors: Dimitrios Zarpalas, Anastasios Zafeiropoulos, Petros Daras, Nicos Maglaveras

Abstract:

Segmentation techniques based on Active Contour Models have been strongly benefited from the use of prior information during their evolution. Shape prior information is captured from a training set and is introduced in the optimization procedure to restrict the evolution into allowable shapes. In this way, the evolution converges onto regions even with weak boundaries. Although significant effort has been devoted on different ways of capturing and analyzing prior information, very little thought has been devoted on the way of combining image information with prior information. This paper focuses on a more natural way of incorporating the prior information in the level set framework. For proof of concept the method is applied on hippocampus segmentation in T1-MR images. Hippocampus segmentation is a very challenging task, due to the multivariate surrounding region and the missing boundary with the neighboring amygdala, whose intensities are identical. The proposed method, mimics the human segmentation way and thus shows enhancements in the segmentation accuracy.

Keywords: Medical imaging & processing, Brain MRI segmentation, hippocampus segmentation, hippocampus-amygdala missingboundary, weak boundary segmentation, region based segmentation, prior information, local weighting scheme in level sets, spatialdistribution of labels, gradient distribution on boundary.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1731
336 Multidimensional Sports Spectators Segmentation and Social Media Marketing

Authors: B. Schmid, C. Kexel, E. Djafarova

Abstract:

Understanding consumers is elementary for practitioners in marketing. Consumers of sports events, the sports spectators, are a particularly complex consumer crowd. In order to identify and define their profiles different segmentation approaches can be found in literature, one of them being multidimensional segmentation. Multidimensional segmentation models correspond to the broad range of attitudes, behaviours, motivations and beliefs of sports spectators, other than earlier models. Moreover, in sports there are some well-researched disciplines (e.g. football or North American sports) where consumer profiles and marketing strategies are elaborate and others where no research at all can be found. For example, there is almost no research on athletics spectators. This paper explores the current state of research on sports spectators segmentation. An in-depth literature review provides the framework for a spectators segmentation in athletics. On this basis, additional potential consumer groups and implications for social media marketing will be explored. The findings are the basis for further research.

Keywords: Multidimensional segmentation, social media, sports marketing, sports spectators segmentation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2579