scholarly journals Comparison of Viola-Jones Haar Cascade Classifier and Histogram of Oriented Gradients (HOG) for face detection

2020 ◽  
Vol 732 ◽  
pp. 012038 ◽  
Author(s):  
C Rahmad ◽  
R A Asmara ◽  
D R H Putra ◽  
I Dharma ◽  
H Darmono ◽  
...  
Keyword(s):  
Face Detection ◽  
Histogram Of Oriented Gradients ◽  
Cascade Classifier ◽  
Haar Cascade

scholarly journals Visitor/Intruder Monitoring System using Haar-cascade Classifier Algorithm

2020 ◽  
pp. 229-231
Author(s):  
Jenifa G ◽  
Yuvaraj N ◽  
SriPreethaa K R
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
Monitoring System ◽  
Face Detection ◽  
Security System ◽  
Machine Learning Algorithms ◽  
Advanced Technology ◽  
Cascade Classifier ◽  
Home Security ◽  
Haar Cascade

Home security system plays a predominant role in the modern era. The purpose of the security systems is to protect the members of the family from intruders. The main idea behind this system is to provide security for residential areas. In today’s world securing our home takes a major role in the society. Surveillance from home to huge industries, plays a significant role in the fulfilment of our security. There are many machine learning algorithms for home security system but Haar-cascade classifier algorithm gives a better result when compared with other machine learning algorithm This system implements a face recognition and face detection using Haar-cascade classifier algorithm, OpenCV libraries are used for training and testing of the face detection process. In future, face recognition will be everywhere in the world. Face recognition is creating a magic in every field with its advanced technology. Visitor/Intruder monitoring system using Machine Learning is used to monitor the person and find whether the person is a known or unknown person from the captured picture. Here LBPH (Local Binary Pattern Histogram) Face Recognizer is used. After capturing the image, it is compared with the available dataset then their respective name and picture is sent to the specified email to alert the owner.

scholarly journals Pendeteksi Wajah Secara Real Time pada 2 Degree of Freedom (DOF) Kepala Robot Menggunakan Deep Integral Image Cascade

CYCLOTRON ◽  
2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Dwi Agung Ayubi ◽  
Dwi Arman Prasetya ◽  
Irfan Mujahidin
Keyword(s):  
Real Time ◽  
Face Detection ◽  
Humanoid Robot ◽  
Degree Of Freedom ◽  
Raspberry Pi ◽  
Cascade Classifier ◽  
Integral Image ◽  
Haar Cascade ◽  
Time Accuracy ◽  
Face Detector

Abstrak— Teknologi Robot merupakan karya terbaik yang sangat penting bagi kehidupan manusia modern saat ini untuk mempermudah semua pekerjaan manusia. Perkembangan dunia robot saat ini akan difokuskan pada robot yang memiliki fitur mirip manusia. Bahkan diharapkan memiliki kemampuan berinteraksi dan berperilaku seperti manusia yaitu robot humanoid, mekanisme dari gerakan robot humanoid memiliki derajat kebebasan Degree of Freedom (DOF). Layaknya pada manusia robot diberi kemampuan penglihatan untuk mendeteksi adanya objek yang ditangkap secara real time Penelitian kepala robot 2 degree of freedom (DOF) untuk pendeteksi wajah secara real time menggunakan metode Deep Integral Image Cascade untuk deteksi wajahnya. Untuk keakurasian pendeteksi wajah dengan real time pada penelitian ini dengan pengujian akurasi terbesar adalah 95,25% dengan waktu respons pendeteksi tercepat 7 detik dengan waktu terlama 8,55 second rata-rata data citra semuanya tidak terdeteksi dengan benarKata kunci: Raspberry pi, Pendeteksi wajah, Degree of freedom, Haar cascade classifier, Robot kepalaAbstract— Robot technology is the best work that is very important for modern human life today to facilitate all human work. The development of the robot world today will be focused on being a robot that has human-like features. Even expected to have the ability to interact and behave like a humanoid robot, the mechanism of humanoid robot movement has a degree of freedom of Degree of Freedom (DOF). Like in the robot man is given the ability of vision to detect the presence of objects captured in real time robotic head Research 2 degree of freedom (DOF) for face detection in real time using the Deep Integral Image Cascade method to Face Detection.  For the real-time accuracy of the face detector in this research with the greatest precision testing is 95.25% with the fastest detection response time of 7 seconds with the oldest time 8.55 second the average image data everything is not detected with Really.Keywords: Raspberry Pi, face detector, Degree of freedom, Haar Cascade classifier, Robot head

scholarly journals REAL TIME FACE DETECTION AND RECOGNITION SYSTEM USING HAAR CASCADE CLASSIFIER AND NEURAL NETWORKS

2021 ◽  
Vol 9 (1) ◽  
pp. 224-231
Author(s):  
Anirban Chakraborty, Shilpa Sharma
Keyword(s):  
Face Detection ◽  
Facial Recognition ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Smart Device ◽  
Cascade Classifier ◽  
Face Detection And Recognition ◽  
Haar Cascade ◽  
The Times ◽  
Detection And Recognition

Home protection and privacy have become one of the most critical aspects in today's world. As technology progresses at an exponential pace, the times are not far ahead for each house to be fitted with sophisticated security systems to deal with regular burglary and theft. But as one side of the tech progresses, so do its detrimental counterparts. DES encryption can be an indicator of how easily an encrypted piece of information can be deciphered. Not long after its release, DES encryption was referred to as 'unsafe' and with today's modern application, anything like DES might be an open invitation to hack. With many developments in the field, the technology has, in many respects, surpassed the use of biometrics (finger prints). Face recognition, nowadays, is present in almost every smart device that has some piece of information stored that holds importance to its users. With facial recognition gaining popularity, many tech companies have come with their own patent to make a technology related to Facial Recognition on the market. This paper suggests a somewhat related concept as to how home protection can be improved by using a face detection and recognition algorithm (Haar Cascade Classifier).

scholarly journals Detection of Iris Localization in Facial Images Using Haar Cascade Circular Hough Transform

2020 ◽  
Vol 55 (4) ◽  
Author(s):  
Haider Shamil ◽  
Bassam Al Kindy ◽  
Amel H. Abbas
Keyword(s):  
Face Detection ◽  
Hough Transform ◽  
High Speed ◽  
Suggested Method ◽  
Cascade Classifier ◽  
Adaboost Algorithm ◽  
Circular Hough Transform ◽  
Haar Cascade ◽  
Iris Center ◽  
Facial Images

In numerous science applications, face detection and iris extraction have been recognized as crucial stages by getting more consideration among researchers as it has an important job. This paper presents an automatic detection method of the iris and its center detection by applying the Haar Cascade Classifier and the Circular Hough Transform algorithm. The suggested method is divided into two primary methodologies: face recognition utilizes the Haar Cascade Classifier and iris extraction using the Hough Transform. The system detects the face from a set of facial images using an Impa-faced dataset. The improved AdaBoost algorithm constructs a cascaded classifier for face detection. Then, by applying the Haar Cascade to obtain an eye pair region and a Hough transform for iris detection by extracting Haar features. Finally, the improved circular Hough transform algorithm locates the iris center. The experimental results of the suggested method show a high-speed, robust ability to acquire the coordinates of the iris center accurately under various illumination changes on different states of human images. The overall accuracy for locating the iris center was 98.75%.

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