scholarly journals Face Detection Using Viola Jones Algorithm

2020 ◽  
Vol 6 (11) ◽  
pp. 131-134
Author(s):  
Dherya Bengani and Prof. Vasudha Bah
Keyword(s):  
Computer Vision ◽  
Face Detection ◽  
Integral Image ◽  
Haar Features ◽  
Computer Vision Technology

Face detection is one of the most widely researched topics in recent times and is at the helm of the computer vision technology. This paper aims to review and study in detail the implementation of Viola Jones algorithm to detect faces in Realtime. Viola Jones algorithm is reviewed first followed by its main steps which include Haar features, integral image and cascading classifiers.

scholarly journals Pengenalan Pola Bentuk Wajah dengan OpenCV

2020 ◽  
Vol 3 (2) ◽  
pp. 181
Author(s):  
Tengku Cut Al-Saidina Zulkhaidi ◽  
Eny Maria ◽  
Yulianto Yulianto
Keyword(s):  
Computer Vision ◽  
Open Source ◽  
Cascade Classifier ◽  
Integral Image ◽  
Haar Features

Pada penelitian ini akan menggunakan module OpenCV pada bahasa pemrograman python untuk mengenali wajah sesorang yang menggunakan Haar Cascades untuk mengenali bentuk wajah dan mata. Tahapan awal menggunakan open source dari intel untuk data wajah dan mata, dipadukan dengan module cascade classifier pada openCV untuk merubah data menjadi pengenalan bentuk wajah dari titik pada wajah yang dianggap sesuai dengan data yang telah disediakan. Banyak dari beberapa sistem pendeteksian wajah menggunakan metode computer vision sebagai metode pendeteksi objek. Metode computer vision dikenal memiliki kecepatan dan keakuratan yang tinggi karena menggabungkan beberapa konsep (Haar Features, Integral Image, AdaBoost, dan Cascade Classifier) menjadi sebuah metode utama untuk mendeteksi objek. Banyak dari sistem deteksi tersebut menggunakan C atau C++ sebagai bahasa pemrograman, dan OpenCV sebagai librari deteksi objek. Hal ini dikarenakan librari OpenCV menerapkan metode computer vision kedalam sistem deteksinya,  sehingga memudahkan dalam pembuatan sistem. Penelitian ini bertujuan untuk  mengimplementasikan computer vision  ke dalam sistem deteksi wajah sederhana dengan memanfaatkan library yang ada pada OpenCV dan memanfaatkan bahasa pemrograman Python sebagai pondasi sistem.

scholarly journals A Review on Computer Vision Technology for Monitoring Poultry Farm – Application, Hardware, and Software

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Nur Syazarin Natasha Abd Aziz ◽  
Salwani Mohd Daud ◽  
Rudzidatul Akmam Dziyauddin ◽  
Mohamad Zulkefli Adam ◽  
Azizul Azizan
Keyword(s):  
Computer Vision ◽  
Poultry Farm ◽  
Computer Vision Technology

scholarly journals Survey of rice seed quality analysis for varietal purity estimation by using image processing techniques

2018 ◽  
Vol 7 (1.7) ◽  
pp. 34
Author(s):  
S. Durai ◽  
C. Mahesh ◽  
T. Sujithra ◽  
A. Suresh
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
South India ◽  
Seed Quality ◽  
Quality Analysis ◽  
Rice Seed ◽  
Two Factors ◽  
Computer Vision Technology ◽  
Processing Techniques ◽  
Varietal Purity

 In south India rice is the major food source and in agriculture, rice production covers more than 70 percentages of entire forming. But in recent the production only from south India not enough to satisfy the need of all, such a huge demand is there. The better production comes from the selection of good seeds. Up to now formers depend on two factors for selecting better seeds, One is the brand which is approved by some quality standards and second one is analyzed manually by experienced people. Both are risky one, we are not pretty much sure the accuracy of analyze. The second one is seeing and feeling. The inspection is not consistent also very time consuming. In the other way we can use computer vision technology to analyze the quality of the seeds. In recent years many of the big industries they are using computer vision technology with Digital Image Processing for many of the applications. In this Paper we are going to discuss the different seed quality analyzing methods and accuracy of result also. Moreover there are different factors and features are there for it, here we are going to study about varietal purity estimation by different methods.

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

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 Optical Crackmeter for Retaining Wall in a Landslide Area Using Computer Vision Technology

2021 ◽  
Vol 33 (3) ◽  
pp. 995
Author(s):  
Yu-Chin Chen ◽  
I-Hui Chen ◽  
Jun-Yang Chen ◽  
Miau-Bin Su
Keyword(s):  
Computer Vision ◽  
Retaining Wall ◽  
Landslide Area ◽  
Computer Vision Technology
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