Smart Parking: Symbol Detection Using Haar Cascade Classifier Algorithm To Monitor Empty Parking Slots

2021 ◽  
Author(s):  
Siti Sendari ◽  
Fajar Kelana Buana ◽  
I Made Wirawan ◽  
Fauzy Satrio Wibowo ◽  
Tibyani
Keyword(s):  
Cascade Classifier ◽  
Symbol Detection ◽  
Smart Parking ◽  
Haar Cascade

scholarly journals Smart Parking Guidance System Using 360o Camera and Haar-Cascade Classifier on IoT System

2019 ◽  
Vol 8 (2S11) ◽  
pp. 864-872 ◽  
Keyword(s):  
Video Processing ◽  
Guidance System ◽  
Raspberry Pi ◽  
Parking Space ◽  
Shopping Malls ◽  
Cascade Classifier ◽  
Parking System ◽  
Parking Lot ◽  
Smart Parking ◽  
Haar Cascade

Nowadays, smart parking guidance system is a crucial research for people’s convenience. The main objective of this research is to develop and analyze on a smart parking guidance system where current available system was compared to this new proposed system. Limited parking space has become serious issue since the number of Malaysia’s populations who are using car keep increasing. Some of the big companies, shopping malls and other public facilities already deployed a smart parking system on their building. However, there are still a lot of buildings that do not own it because the system required a lot of investment, where the huge parking areas need higher cost to install sensors on each parking lot available. The proposed smart parking guidance system in this research was depending on a 360° camera that was modified on raspberry pi camera module and 360o lens and Haar-Cascade classifier. The image and video processing was by Open CV and python program to detect the available parking space and cloud firebase was used to update data where users can access the parking space availability by android mobile phone specifically at a closed parking space. A single 360°camera was replaced several sensors and camera which was implemented on traditional smart parking system. An analysis was done on the performance of the system where it can detect the parking availability with 99.74% accuracy and which is far better than conventional system including reliability and cost for the parking space guidance system.

Smart Parking System Based on Haar Cascade Classifier and SIFT Method

2021 ◽  
Author(s):  
Rahmat Fauzi Yulianto ◽  
Arif Irwansyah ◽  
Ni'am Tamami
Keyword(s):  
Cascade Classifier ◽  
Parking System ◽  
Smart Parking ◽  
Haar Cascade

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 Smart Parking Guidance System on IoT

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2793-2798 ◽  
Keyword(s):  
Video Processing ◽  
Guidance System ◽  
Raspberry Pi ◽  
Parking Space ◽  
Shopping Malls ◽  
Public Facilities ◽  
Parking System ◽  
Parking Lot ◽  
Smart Parking ◽  
Haar Cascade

Nowadays, smart parking guidance system is a crucial research for people’s convenience where the integrating concept of IoT that include hardware and software with the connection of internet for image or video processing technology is a powerful application which made up a complete smart parking system. The main objective of this research is to develop and analyze on a smart parking guidance system where current available system was compared to this new proposed system. Limited parking space has become serious issue since the number of Malaysia’s populations are using car keep increasing. Some of the big companies, shopping malls and other public facilities already deployed a smart parking system on their building. However, there are still a lot of buildings that do not own it because the system required a lot of investment, where the huge parking areas need higher cost to install sensors on each parking lot available and cameras are costly and lower in reliability. The proposed smart parking guidance system in this research was depending on a 360° camera that was modified on Raspberry Pi camera module and 360o lens that process with De-Warping techniques for the normal view rather than 360-degree view and Haar-Cascade classifier. The image and video processing was done by Open CV and python program to detect the available parking space and cloud firebase was used to update data where users can access the parking space availability by android mobile phone specifically at a closed parking space. A single 360°camera was replaced several sensors and cameras which were implemented on traditional parking guidance system. In the end of the paper, it is proved that prototype based smart parking is the convenient way to find the parking space availability.

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