scholarly journals Human Authentication using Face, Voice and Fingerprint Biometrics

2021 ◽  
Vol 9 (VII) ◽  
pp. 853-862
Author(s):  
Dr. Dinesh Kumar D S
Keyword(s):  
Recognition Performance ◽  
Code Word ◽  
Fingerprint Recognition ◽  
Cascade Algorithm ◽  
Minutiae Extraction ◽  
Fingerprint Biometrics ◽  
Haar Cascade ◽  
Nearest Neighbour Classifier ◽  
Matching Score ◽  
The Voice

Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the system consider the person as authorized person. Fusion at matching score level is then applied to enhance recognition performance. In particular, we employ the product rule in our investigation. The final identification is then performed using a nearest neighbour classifier which is fast and effective. Experimental results confirm that our approach achieves excellent recognition performance, and that the fusion approach outperforms biometric identification based on single modalities.

scholarly journals Computer Vision Based Industrial Robotic Arm for Sorting Objects by Color and Height

2020 ◽  
Vol 01 (04) ◽  
pp. 116-122
Author(s):  
Abu Salman Shaikat ◽  
Suraiya Akter ◽  
Umme Salma
Keyword(s):  
Computer Vision ◽  
Production Process ◽  
Production Systems ◽  
Robotic Arm ◽  
Cascade Algorithm ◽  
Manual Sorting ◽  
System Requirement ◽  
Conveyor Belts ◽  
Haar Cascade ◽  
A New Technique

In industrial production systems, manufacturers often face difficulties in sorting different types of objects. Color and height-based sorting which is done manually by human is quite a tedious task and its needs countless time as well. For manual sorting, many workers are required, which can be quite expensive. Moreover, robots that can sort only color or height can’t be effective when there is a need of products with same color with different heights and vice versa. In this paper, a computer vision based robotic sorter is proposed, which is capable of detecting and sorting objects by their colors and heights at the same time. This work isn’t done before as height sorting of same shapes is a new technique, which is done with color sorting techniques by computer vision. It is equipped with a robotic arm having 6 degree of freedom (DOF), by which it picks up and then place objects according to its color and height, to a predetermined place as per the production system requirement. A camera with the computer vision software detects various colors and heights. Haar Cascade algorithm has been used to sort the products. This multi-DOF robotic sorter can be a remarkably useful tool for automating the production process completely, where multiple conveyor belts are used, which can reduce time complexity as well. In the proposed system, the efficiency of color and height sorting is around 99%, which proves the efficiency of our system. The overall improvement in the efficiency of the production process can be significantly enhanced by using this system.

AUTHENTICATION OF FINGERPRINT BIOMETRICS ACQUIRED USING A CELLPHONE CAMERA: A REVIEW

2013 ◽  
Vol 11 (05) ◽  
pp. 1350033 ◽  
Author(s):  
MOHAMMED S. KHALIL ◽  
FAJRI KURNIAWAN ◽  
KASHIF SALEEM
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
High Performance ◽  
Personal Information ◽  
Current Trend ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Biometrics ◽  
Smart Mobile Phone ◽  
Smart Mobile

Over the past decade, there have been dramatic increases in the usage of mobile phones in the world. Currently available smart mobile phones are capable of storing enormous amounts of personal information/data. The smart mobile phone is also capable of connecting to other devices, with the help of different applications. Consequently, with these connections comes the requirement of security to protect personal information. Nowadays, in many applications, a biometric fingerprint recognition system has been embedded as a primary security measure. To enable a biometric fingerprint recognition system in smart mobile phones, without any additional costs, a built-in high performance camera can be utilized. The camera can capture the fingerprint image and generate biometric traits that qualify the biometric fingerprint authentication approach. However, the images acquired by a mobile phone are entirely different from the images obtained by dedicated fingerprint sensors. In this paper, we present the current trend in biometric fingerprint authentication techniques using mobile phones and explore some of the future possibilities in this field.

CLASSIFIER COMBINATION AND ITS APPLICATION IN IRIS RECOGNITION

2008 ◽  
Vol 22 (03) ◽  
pp. 617-638 ◽  
Author(s):  
XINHUA FENG ◽  
XIAOQING DING ◽  
YOUSHOU WU ◽  
PATRICK S. P. WANG
Keyword(s):  
Iris Recognition ◽  
Recognition Accuracy ◽  
Recognition Performance ◽  
Recognition System ◽  
Classifier Combination ◽  
Practical Application ◽  
Finite Samples ◽  
Biometric Systems ◽  
Matching Score ◽  
Combined Classifier

Classifier combination is an effective method to improve the recognition accuracy of a biometric system. It has been applied to many practical biometric systems and achieved excellent performance. However, there is little literature involving theoretical analysis on the effectiveness of classifier combination. In this paper, we investigate classifiers combined with the max and min rules. In particular, we compute the recognition performance of each combined classifier, and illustrate the condition in which the combined classifier outperforms the original unimodal classifier. We focus our study on personal verification, where the input pattern is classified into one of two categories, the genuine or the impostor. For simplicity, we further assume that the matching score produced by the original classifier follows a normal distribution and the outputs of different classifiers are independent and identically distributed. Randomly-generated data are employed to test our conclusion. The influence of finite samples is explored at the same time. Moreover, an iris recognition system, which adopts multiple snapshots to identify a subject, is introduced as a practical application of the above discussions.

Finger Vein Recognition Based on Stable and Discriminative Superpixels

2016 ◽  
Vol 30 (06) ◽  
pp. 1650015 ◽  
Author(s):  
Lizhen Zhou ◽  
Gongping Yang ◽  
Yilong Yin ◽  
Lu Yang ◽  
Kuikui Wang
Keyword(s):  
Recognition Performance ◽  
Fusion Method ◽  
Recognition Method ◽  
Biometric Technology ◽  
Training Images ◽  
Finger Vein ◽  
Vein Recognition ◽  
Matching Score ◽  
Finger Vein Recognition ◽  
Better Than

Finger vein pattern, as a promising hand-based biometric technology, has been well studied in recent years. In this paper, a new superpixel-based finger vein recognition method is presented. In the proposed method, we develop two types of effective superpixels, i.e. stable superpixel and discriminative superpixel to represent finger vein image and these superpixels are expected to play different roles in matching stage. In detail, the stable and discriminative superpixels are firstly learned from the training images for each enrolled class. When verifying a testing image, we just compare the superpixels at the same location as the two types of superpixels in template. Then, the two types of superpixels are combined utilizing a reversible weight-based fusion method in score level. Additionally, to further improve the recognition performance, we explore the superpixel context feature (SPCF). For each superpixel the SPCF is obtained by comparing the current superpixel with its surrounding neighbors. In the final matching stage, we integrate the matching score of two types of superpixels and it of the SPCF using the weighted SUM fusion method. The experimental results on two open finger vein databases, i.e. PolyU and SDUMLA-FV, show that our method not only performs better than the existing superpixel-based method, but also has advantages in comparison with some traditional ones.

scholarly journals Social Distancing for Covid-19 Monitoring System

2021 ◽  
pp. 49-61
Author(s):  
Raj Kushwaha ◽  
Kismat Khatri ◽  
Yogesh Mahato
Keyword(s):  
Real Time ◽  
Safe Distance ◽  
Public Places ◽  
Cascade Algorithm ◽  
Facial Mask ◽  
Social Distancing ◽  
Video Footage ◽  
Camera Systems ◽  
Haar Cascade ◽  
Increasing Demand

The battle of corona-virus and mankind is possible to be tackled as long as we maintain the basic norm of social distancing and wearing masks amongst ourselves as it is through our droplets from the respiratory tract that the virus spreads. With the increasing demand for man-force and people requiring to go to their workplaces post lockdown, it is very necessary that we save each other from the virus. In this project, we will go through a detailed explanation of how we can use Python, AI and Deep Learning to monitor social distancing at public places and workplaces are keeping a safe distance from each other by analyzing real-time video streams from the camera and also detect facial mask monitoring using OpenCV and Python. To ensure if people are following social distancing protocols in public places and workplaces, we wanted to develop a tool that can monitor if people are keeping a safe distance from one another, wearing masks or not by processing real-time video footage from the camera. People at workplaces, factories, shops can integrate this tool into their security camera systems and can monitor whether people are keeping a safe distance from each other or not along with that we detect facial mask monitoring using Python with help of haar-cascade algorithm to see whether a person is wearing a mask or not. We are also planning to include thermal screening detection to measure the temperature of the subjects, a dashboard which will display a live report of corona cases around the world. We will also include an alert system that will send a notification to the authorities if the social distancing is not followed or if the temperature exceeds the threshold. The authorities can take suitable measures to isolate the subject and thus prevent the spread of Covid-19.

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