scholarly journals An ear recognition system based on local wavelet subband energy distribution

2021 ◽  
Vol 24 (2) ◽  
pp. 1212
Author(s):  
Ruaa Isam Fadhil ◽  
Loay E. George
Keyword(s):  
Energy Distribution ◽  
Recognition Rate ◽  
Low Frequency ◽  
Recognition System ◽  
Individual Identification ◽  
Full Description ◽  
Ear Recognition ◽  
Biometric Characteristic ◽  
Human Ear ◽  
Selection Of

The outer ear features have been used for many years in forensic science of recognition. Human ear is a valuable information provenance of data for individual identification/authentication. Ear meets biometric characteristic (universality, distinctiveness, permanence and collectability). Biometric system depending on ear image facing two major challenges; the first one is the localization of human ear area in given profile face image, and the second one is the selection of proper features to distinguish between individuals. In this work, we propose an alogorithm for ear recognition based on the local spatial energy distribution of wavelet sub-bands, because of wavelet transform has the ability to analyze the local feature of 2-D image by determining where the low frequency and high frequency areas are and it provides full description of the spatial distribution of the ear image. Nearest classifier are used to make a recognition decision in matching stage. The system was tested over a public database consist of 493 images. The attained recognition rate was (95.28%) and the achieved minimum equal error rate (EER) is 0.02%.

A Study of Different Methodologies Helpful in the Identification of Offline Handwritten Script

2018 ◽  
Vol 6 (6) ◽  
pp. 307
Author(s):  
Manish M. Kayasth ◽  
Bharat C. Patel
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Post Processing ◽  
Classification Technique ◽  
Scanned Image ◽  
Gujarati Language ◽  
High Degree ◽  
Selection Of

The entire character recognition system is logically characterized into different sections like Scanning, Pre-processing, Classification, Processing, and Post-processing. In the targeted system, the scanned image is first passed through pre-processing modules then feature extraction, classification in order to achieve a high recognition rate. This paper describes mainly on Feature extraction and Classification technique. These are the methodologies which play an important role to identify offline handwritten characters specifically in Gujarati language. Feature extraction provides methods with the help of which characters can identify uniquely and with high degree of accuracy. Feature extraction helps to find the shape contained in the pattern. Several techniques are available for feature extraction and classification, however the selection of an appropriate technique based on its input decides the degree of accuracy of recognition. 

scholarly journals Human – Ear Recognition Using Scale Invariant Feature Transform

2021 ◽  
pp. 1-12
Author(s):  
Abbas Hassin ◽  
Dheyaa Abbood
Keyword(s):  
Distance Measure ◽  
Recognition System ◽  
Scale Invariant Feature Transform ◽  
Morphological Operations ◽  
Scale Invariant ◽  
Ear Recognition ◽  
Invariant Feature ◽  
Feature Transform ◽  
Human Ear ◽  
Scale Invariant Feature

Biometrics techniques are the standard of a wide group of many applications for a human’s identification and verification issues. Because of this reason, a high scale of security needs to search for a new way to identify the person arises. In this paper, establish a human ear recognition system is proposed. This system combines four main phases: ear detection, ear feature extraction, ear recognition, and confirmation. The essential of the proposed system is to divide the ear image into the skin and non-skin pixels using a likelihood skin detector. The likelihood image processes by morphological operations to complete ear regions.  Scale-invariant feature transform uses for extracting the fixed features of the ear. Ear recognition includes two modes identification mode and verification mode. Euclidean Distance Measure (EDM) uses for similarity measure between the first image in the database and a new image. According to the three experiments conducted in this paper, the results of the different datasets, the accuracy ratio are 100%, 92%.and 92% respectively.

Human Ear Recognition System

2015 ◽  
pp. 5475-5481
Author(s):  
Durgesh Singh ◽  
Sanjay Kumar Singh
Keyword(s):  
Recognition System ◽  
Personal Identification ◽  
Law Enforcement Agencies ◽  
Ear Recognition ◽  
Knowledge Based ◽  
Ear Detection ◽  
Biometric Systems ◽  
Identity Based ◽  
Human Ear ◽  
Traditional Approaches

A reliable human recognition scheme is required in wide variety of systems to either verify or identify the identity of an individual requesting their services. Using traditional approaches such as possession based and knowledge based systems, it is very difficult to differentiate between an authorized person and an impostor. This is a strong reason for replacing traditional ID-based systems with biometric systems which are based on human traits that cannot be denied, stolen, or faked easily. Biometric recognition refers to the automatic recognition, based on physiological and /or behavioral characteristics of an individual. By using biometrics, it is possible to establish an individual's identity based on “who he or she is” rather than by “what he or she possesses likes smart card” or “what he or she remembers likes password.” Human ear due to its consistent behavior over the age, has gained much popularity in recent years among various physiological biometric traits. The decidability index of the ear has been found that magnitude significant greater than that of face. Ear remarkably consistent and does not change its shape under expressions like face. The shape of the outer ear is recognized as a valuable means for personal identification. Naturally, an ear biometric system consists of ear detection and ear recognition modules. Ear biometric has played an important role for many years in forensic science and its use by law enforcement agencies.

scholarly journals A Gabor Wavelet Based Approach for Off-Line Recognition of ODIA Handwritten Numerals

2018 ◽  
Vol 7 (2.32) ◽  
pp. 253
Author(s):  
Abhisek Sethy ◽  
Prashanta Kumar Patra ◽  
Soumya Ranjan Nayak ◽  
Deepak Ranjan Nayak
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Feature Vector ◽  
Rbf Neural Network ◽  
Probabilistic Approach ◽  
Recognition Rate ◽  
Recognition System ◽  
Gabor Wavelet ◽  
Gabor Wavelet Transformation ◽  
Selection Of

Optical Character Recognition is one of the most interesting and highly motivated areas of research, which has been very much ap-preciated in different aspect to the area of digitations world. Here in this paper we have suggested a probabilistic approach for develop-ing recognition system for handwritten Odia numerals. To report a good  level of recognition of Odia scripts is quite challenging with respect to other Indian scripts .All the procedure are sequentially enclosed to develop an recognition model and report a successful recognition accuracy. Here we have performed the analysis over to standard handwritten numeral database named as IITBBS Odia Numeral Database, which is collected from IIT Bhubaneswar. In the suggestive recognition system we have adopted a 2D-Gabor wavelet transformation approach for selection of feature vector. Apart from it we have also noted down the dimensional reduction to the obtained feature vector by sustaining to PCA. In order to predict high recognition rate we have followed up by RBF Neural Network classifier. In addition to it we have also evaluate different version of RBF like Gaussian and Polynomial. Performing over 400 samples each of 10 categories (400*10) number of Odia numeral images, we have maintained a well-defined training and testing ratio in the clas-sifier and achieved 98.02%, 96.8%.recognition rate for the reported classifiers.  

Development of a Modified Ear Recognition System for Personnel Identification

2020 ◽  
Vol 13 ◽  
Author(s):  
Mais Al-Sharqi ◽  
Haitham Sabah Hasan
Keyword(s):  
Recognition Accuracy ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Identification System ◽  
Segmentation Method ◽  
False Acceptance Rate ◽  
Ear Recognition ◽  
Human Ear ◽  
Algorithm Implementation

Aims: This study examined the development of a match region localization (MRL) ear recognition system (ERS). Background: The developed algorithm is called the match region localization (MRL) algorithm. MRL recognizes a human ear using only small visible portions of the ear while excluding covered or occluded portions. The MRL technique divides an ear image into segments of small blocks; these blocks are either regular (and equally sized) segments or irregularly shaped blocks depending on the adopted segmentation method. Objective: The recognition accuracy of the system is 97.07%, thereby implying that the system can perform efficiently as an identification system. Method: This research follows four major stages, namely, development of a PCA-based ear recognition algorithm, implementation of the developed algorithm, determination of the optimum ear segmentation method, and evaluation of the performance of the technique. Results: The False acceptance rate (FAR) of the developed ear recognition system (ERS) is 0.06. This result implies that six out of every 100 intruders will be falsely accepted. Conclusion: The developed ERS outperforms the existing ERS by approximately 24.61% in terms of system recognition accuracy; the developed ERS can be tested on other publicly available ear databases to check its performance on larger platforms. Other: The developed ERS can be tested on other publicly available ear databases to check its performance on larger platforms.

Human Ear Recognition Using Hybrid Filter and Supervised Locality Preserving Projection

2012 ◽  
Vol 529 ◽  
pp. 271-275
Author(s):  
Song Ze Lei ◽  
Qiang Zhu
Keyword(s):  
Gabor Filter ◽  
Recognition Rate ◽  
Difficult Problem ◽  
Hybrid Filter ◽  
Locality Preserving Projection ◽  
Ear Recognition ◽  
Locality Preserving ◽  
Discriminative Feature ◽  
Human Ear ◽  
Log Gabor

To solve the difficult problem of human ear recognition caused by variety of ear angle, a novel method which combines hybrid filter with supervised locality preserving projection (SLPP) is proposed. The ear image is firstly filtered by Log-Gabor filter which is constructed with 5 scales and 8 orientations. The important parameters of Log-Gabor filter are selected through experiments. To form effective and discriminative feature too many Log-Gabor coefficients are reduced by discrete cosine transform. Lastly feature is constructed by SLPP to discovery geometrical rules. Experimental results show that compared with the traditional methods, the proposed method obtains higher recognition rate, and is robust to multi-pose of ear recognition.

Human Ear Recognition Based on Phase Congruency and Kernel Discriminant Analysis

2012 ◽  
Vol 241-244 ◽  
pp. 1614-1617
Author(s):  
Song Ze Lei ◽  
Qiang Zhu
Keyword(s):  
Discriminant Analysis ◽  
Gabor Filter ◽  
Recognition Rate ◽  
High Dimensional ◽  
Dimensional Vector ◽  
Phase Congruency ◽  
Kernel Discriminant Analysis ◽  
Ear Recognition ◽  
Novel Method ◽  
Human Ear

To solve the multi-pose ear recognition problem under the different illumination condition, a novel method which combines phase congruency with kernel discriminant analysis (KDA) is proposed. The phase congruency of ear image is first calculated using Log-Gabor filter with 5 scales and 8 orientations, and then the phase congruency of different orientation is constructed as high dimensional vector including ample information. The high dimensional vector is mapped to kernel space to acquire discriminant feature. Experimental results show that the proposed method obtains higher recognition rate compared with the other related methods. The method of the phase congruency can eliminate the influence of illumination and phase congruency with KDA is effective to multi-pose ear recognition.

Sign in / Sign up

Export Citation Format

Share Document