scholarly journals Secure Online Transaction using Iris

2021 ◽  
Vol 1 (2) ◽  
pp. 5-14
Author(s):  
Abhishek Balamurugan ◽  
◽  
Sai Dhanush. R ◽  
Sundeep J ◽  
Sivasankari. K ◽  
...  
Keyword(s):  
Haar Cascade

In this project, we are planning to create a strong robust calculation for executing cash in higher level security reason with high acknowledgment rates in a shifting environment. To begin with, Haar cascade based calculation has been connected for quick and basic confront location from the input picture. The confront picture is at that point being changed over into grayscale picture. After that, the iris, eyebrows, nose, mouth of candidates are extricated from the escalated valleys from the recognized confront.

scholarly journals Pengolahan Citra Digital untuk Keyboard Virtual Sebagai Antarmuka pada Aplikasi Berbasis Web

2015 ◽  
Vol 5 (2) ◽  
pp. 111
Author(s):  
Raksaka Indra Alhaqq ◽  
Agus Harjoko
Keyword(s):  
Image Processing ◽  
Web Application ◽  
Index Finger ◽  
Processing Technology ◽  
White Background ◽  
Cascade Classifier ◽  
Virtual Keyboard ◽  
Image Processing Technology ◽  
Optimal Distance ◽  
Haar Cascade

AbstrakSejak pertama kali komputer ditemukan, keyboard selalu menjadi alat utama yang menjadi penghubung interaksi antara manusia dan komputer. Saat ini banyak komputer yang menerapkan teknologi pengolahan citra untuk menjadikannya perantara interaksi antara komputer dan manusia.Dalam penelitian ini, penulis mencoba untuk menerapkan teknologi pengolahan citra yang digunakan untuk keyboard virtual pada aplikasi web. Digunakan webcam untuk menangkap citra ujung jari telunjuk. Hasil capture citra akan dikirimkan ke server localhost untuk diproses dengan image processing. Untuk mendeteksi ujung jari telunjuk, digunakan metode Haar Cascade Classifier. Proses pendeteksian tersebut menghasilkan koordinat yang akan dikirimkan ke aplikasi web yang selanjutnya dijadikan acuan untuk menentukan posisi tombol pada keyboard virtual. Sehingga keyboard virtual akan menampilan karakter sesuai dengan yang ditunjuk oleh ujung jari telunjuk.Dari hasil pengujian yang dilakukan, jarak optimal ujung jari telunjuk dengan webcam adalah 20 – 35 cm. Derajat kemiringan ujung jari telunjuk untuk dapat terdeteksi antara 0° – 10°. Sistem mampu mengenali ujung jari telunjuk pada ruangan berlatar belakang putih polos dan terdapat sedikit perabot. Waktu respon untuk menampilkan karakter keyboard virtual rata-rata 5,156 detik. Sehingga keyboard virtual pada sistem ini belum mampu dijadikan antarmuka pada aplikasi web, dikarenakan masih sulit digunakan dalam mengarahkan ujung jari telunjuk ke tombol karakter yang diinginkan.Kata kunci—aplikasi web, Haar Cascade Classifier, keyboard virtual, pengolahan citra  AbstractSince the first computer was founded, keyboard is always been a primary tool for interaction between humans and computers. Today, many computers use image processing technology to make interaction between computers and humans.The author try to apply image processing technology that implemented to virtual keyboard on web application. Using a webcam to capture the tip of index finger and the results will be sent to the localhost server for processing with image processing. Using Haar Cascade Classifier method to detect the tip of index finger, it will produce coordinates that sent to the web application and it used as a reference for determining button positions on virtual keyboard. Virtual keyboard characters will display after appointed by the tip of  index finger.From testing results, optimal distance from index finger to webcam is 20 – 35 cm. System can recognize the tip of index finger on white background and room with few furnitures. Average response time for displaying virtual keyboard sentences is 3 minutes and 28.838 seconds. So the virtual keyboard on this system was not able to be used as interface on web application, because it difficult to use in directing the tip of index finger to the character keys.Keywords—web application, Haar Cascade Classifier, virtual keyboard, image processing

scholarly journals PENDETEKSIAN OBJEK ROKOK PADA VIDEO BERBASIS PENGOLAHAN CITRA DENGAN MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER

2018 ◽  
Vol 1 (3) ◽  
pp. 92
Author(s):  
Kadek Oki Sanjaya ◽  
Gede Indrawan ◽  
Kadek Yota Ernanda Aryanto
Keyword(s):  
Image Processing ◽  
Detection System ◽  
High Accuracy ◽  
Special Study ◽  
Cascade Classifier ◽  
Integral Image ◽  
Main Method ◽  
Average Accuracy ◽  
Haar Features ◽  
Haar Cascade

Object detection is a topic widely studied by the scientists as a special study in image processing. Although applications of this topic have been implemented, but basically this technology is not yet mature, futher research is needed to developed to obtain the desired result. The aim of the present study is to detect cigarette objects on video by using the Viola Jones method (Haar Cascade Classifier). This method known to have speed and high accuracy because of combining some concept (Haar features, integral image, Adaboost, and Cascade Classifier) to be a main method to detect objects. In this research, detection testing of cigarettes object is in samples of video with the resolution 160x120 pixels, 320x240 pixels, 640x480 pixels under condition of on 1 cigarette object and condition 2 cigarettes object. The result of this research indicated that percentage of average accuracy highest 93.3% at condition 1 cigarette object and 86,7% in the condition 2 cigarette object that was detected on the video with resolution 640x480 pixels, while the percentage of accuracy lowest 90% at condition 1cigarette object, and 81,7% at the condition 2 cigarette objects, detected on the video with the lowest resolution 160x120 pixels. The percentage of average errors at detection cigarettes object was inversely with percentage of accuracy. So that the detection system is able to better recognize the object of the cigarette, then the number of samples in the database needs to be improved and able to represent various types of cigarettes under various conditions and can be added new parameters related to cigarette object

scholarly journals Real Time Face Recognition based Smart Lab for Energy Conservation

Webology ◽  
2021 ◽  
Vol 18 (SI02) ◽  
pp. 32-41
Author(s):  
M. Karthikeyan ◽  
T.S. Subashini ◽  
M.S. Prashanth
Keyword(s):  
Face Recognition ◽  
Object Identification ◽  
Home Automation ◽  
Human Beings ◽  
Environmentally Conscious ◽  
Repetitive Tasks ◽  
Automation Systems ◽  
The Face ◽  
Identification Technique ◽  
Haar Cascade

Home automation offers a good solution to help conserve our natural resources in a time when we are all becoming more environmentally conscious. Home automation systems can reduce power consumption and when they are not in use automatically turn off lights and appliances. With home automation, many repetitive tasks can be performed automatically or with fewer steps. For example, each time the person gets out of his computer desk, for instance, the fan and the lights need to be turned off and switched on when he comes back to the computer desk. This is a repetitive task, and failure to do so leads to a waste of energy. This paper proposes a security/energy saving system based on face recognition to monitor the fan and lights depending on the presence or absence of the authenticated user. Initially, the authenticated faces/users LBPH (Local Binary Pattern Histogram) features were extracted and modelled using SVM to construct the face profile of all authenticated users. The webcam catches the user's picture before the PC and the Haar-cascade classifier, a profound learning object identification technique is used to identify face objects from the background. The facial recognition techniques were implemented with python and linked to the cloud environment of Ada-Fruit in order to enable or disable the light and fan on the desk. The relay status is transmitted from Ada Fruit Cloud to Arduino Esp8266 using the MQTT Protocol. If the unidentified user in the webcam is detected by this device, the information in the cloud will be set to ' off ' status, allowing light and fan to be switched off. Although Passive Infrared Sensor (PIR) is widely used in home automation systems, PIR sensors detect heat traces in a room, so they are not very sensitive when the room itself is hot. Therefore, in some countries such as INDIA, PIR sensors are unable to detect human beings in the summer. This system is an alternative to commonly used PIR sensors in the home automation process.

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.

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