Image Processing in Road Traffic Analysis

The article presents an application of computer vision methods to traffic flow monitoring and road traffic analysis. The application is utilizing image-processing and pattern recognition methods designed and modified to the needs and constrains of road traffic analysis. These methods combined together gives functional capabilities of the system to monitor the road, to initiate automated vehicle tracking, to measure the speed, and to recognize number plates of a car. Software developed was applied in and approved with video monitoring system, based on standard CCTV cameras connected to wide area network computers

Identifikasi Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Jaringan Syaraf Tiruan Berbasis Citra Digital

Meningkatnya volume kendaraan bermotor yang terjadi saat ini membuat kebutuhan akan adanya sistem yang dapat diterapkan pada banyak aplikasi pemantauan aktivitas lalu lintas dantaranya pembayaran jalan tol elektronik, pelanggaran lalu lintas, pencurian kendaraan dan lain sebagainya. Tujuan dari peneltian ini adalah mengidentifikasi pengenalan karakter plat nomor kendaraan menggunakan Jaringan Syaraf tiruan berbasis citra digital, pengenalan karakter dan keberhasilan proses klasifikasi ditentukan dari keberhasilan ekstraksi fitur tiap karakter sehingga dengan bentuk karakter yang beragam akan menambah tingkat kesulitan dalam proses pengenalan. Pengenalan pola pada plat nomor kendaraan menggunakan métode Jaringan Syaraf Tiruan yang terdiri dari beberapa tahapan, yaitu deteksi lokasi plat nomor, praproses citra plat nomor, memilih data uji dan data latih, indentifikasi menggunkan JST diantaranya Model klasifikasi JST, pengujian JST dan Akurasi JST. Data yang diambil sebanyak 160 yang terdiri atas 40 citra wilayah Bogor (F), 40 citra wilayah Jakarta (B), 40 citra wilayah Bandung (D) dan 40 citra wilayah Purwakarta (T). Data dari masing-masing jenis plat nomor dibagi menjadi dua bagian, 30 buah untuk data latih dan 10 buah untuk data uji. Dari uji coba berdasarkan 40 data latih yang dilakukan terdapat 31 data uji yang terdefinisi atau akurasi sebesar 77,5%. Ekstraksi ciri yang digunakan dalam penelitian ini terdiri atas 6 parameter yaitu nilai entropi, variants, means, red, green dan blue, sedangkan proses identifikasi menggunakan Jaringan Syaraf tiruan. Hasil identifikasi akan menampilkan data uji dengan kode wilayahnya berdasarkan nilai yang terdekat dengan data latih, sehingga mendapatkan hasil 77,5%.Kata Kunci: Multimedia Plat Nomor, Deteksi, JS

An overview of technologies deployed in GCC Countries to combat COVID-19

Since December 2019, COVID-19 and all of its variants continue to ravage the planet with consequent negative impact that has completely changed our lives within a short period of time after the outbreak of the Virus. On March 11, 2020, COVID-19 was declared a global pandemic by the World Health Organization. Since then, a group of new COVID-19 variants has emerged posing a greater danger to humanity. By the start of August 2021, the reported COVID-19 related death toll across the globe has rocketed to 4,233,139. To deal with the COVID-19 pandemic, countries across the world have rushed to develop various techniques in order to embrace an array of solutions to the problem. Covid-19 negatively affected countries in several sectors including industry, business, health, and education to name a few. The Gulf Cooperation Council (GCC) countries are among the top countries which use cutting-edge technologies in several sectors. This significantly helped these countries to overcome the spread of this virus. In this paper, we present an overview of the technologies, techniques, solutions, and strategies deployed by the Gulf Cooperation Council (GCC) countries to combat the COVID-19 pandemic in order to safeguard their citizens and speedy return of life to normalc

An overview of technologies deployed in GCC Countries to combat COVID-19

Since December 2019, COVID-19 and all of its variants continue to ravage the planet with consequent negative impact that has completely changed our lives within a short period of time after the outbreak of the Virus. On March 11, 2020, COVID-19 was declared a global pandemic by the World Health Organisation. Since then, a group of new COVID-19 variants has emerged posing a greater danger to humanity. By the start of August 2021, the reported COVID-19 related death toll across the globe has rocketed to 4,233,139. To deal with the COVID-19 pandemic, countries across the world have rushed to develop various techniques in order to embrace an array of solutions to the problem. Covid-19 negatively affected countries in several sectors including industry, business, health, and education to name a few. The Gulf Cooperation Council (GCC) countries are among the top countries which use cutting-edge technologies in several sectors. This significantly helped these countries to overcome the spread of this virus. In this paper, we present an overview of the technologies, techniques, solutions, and strategies deployed by the Gulf Cooperation Council (GCC) countries to combat the COVID-19 pandemic in order to safeguard their citizens and speedy return of life to normalcy

Mid-term evaluation of the Hercule III programme. CEPS Research Report, February 2018

The Hercule III programme was established by the European Commission to promote activities against fraud, corruption and any other illegal activities affecting the financial interests of the Union. In compliance with Article 13 of Regulation (EU) No 250/2014 establishing the Hercule III Programme, the Evaluation Roadmap prepared by OLAF and the Better Regulation Guidelines, CEPS was commissioned to carry out a mid-term evaluation, together with three other institutes, to assess the relevance, coherence, effectiveness, efficiency, EU added value and sustainability of the programme. Based on primary data collected from 574 stakeholders and extensive desk research, the study concludes that Hercule III scores well in all the evaluation criteria. In addition, the programme appears to indirectly contribute to the targets of the Europe 2020 strategy. Therefore, the evaluation recommends the funding of a new edition of the programme in order to sustain the protection of EU financial interests in the coming years. Whereas no major changes would be required in the structure of the programme, it is advisable to introduce certain improvements to enhance the current performance of Hercule III and its future editions. In this respect, the programme should, inter alia, allocate more resources to protecting EU financial interests on the expenditure side of the budget, fighting against corruption and VAT fraud, fostering cross-border cooperation and procuring and making technical equipment available to national authorities

Intelligent System for Vehicles Number Plate Detection and Recognition Using Convolutional Neural Networks

Vehicles on the road are rising in extensive numbers, particularly in proportion to the industrial revolution and growing economy. The significant use of vehicles has increased the probability of traffic rules violation, causing unexpected accidents, and triggering traffic crimes. In order to overcome these problems, an intelligent traffic monitoring system is required. The intelligent system can play a vital role in traffic control through the number plate detection of the vehicles. In this research work, a system is developed for detecting and recognizing of vehicle number plates using a convolutional neural network (CNN), a deep learning technique. This system comprises of two parts: number plate detection and number plate recognition. In the detection part, a vehicle’s image is captured through a digital camera. Then the system segments the number plate region from the image frame. After extracting the number plate region, a super resolution method is applied to convert the low-resolution image into a high-resolution image. The super resolution technique is used with the convolutional layer of CNN to reconstruct the pixel quality of the input image. Each character of the number plate is segmented using a bounding box method. In the recognition part, features are extracted and classified using the CNN technique. The novelty of this research is the development of an intelligent system employing CNN to recognize number plates, which have less resolution, and are written in the Bengali language.</jats:p

Recognition of Vehicle Number Plates

This work deals with problematic from field of artificial intelligence, machine vision and neural networks in construction of an automatic number plate recognition system. (ANPR). This problematic includes mathematical principles and algorithms, which ensure a process of number plate detection, processes of proper characters segmentation, normalization and recognition. Work comparatively deals with methods achieving invariance of systems towards image skew, translations and various light conditions during the capture. Work also contains an implementation of a demonstration model, which is able to proceed these functions over a set of snapshots.

Automatic recognition of vehicle number plates

Darbā apskatītas attēlu analīzes metodes, kas nepieciešamas numuru analīzē, kā arī soli pa solim apskatīta konkrētas metožu secības pielietojums numuru atpazīšanā. Apskatītās metodes ietver trokšņu filtrus, numura atrašanās vietas noteikšanu, numura stāvokļa noteikšanu un numura normalizāciju. Darbā arī apskatītas metodes, kā atpazīt dinamiskus attēlus. Darba ietvaros izstrādātas divas metodes – līdzīgo kaimiņu metode, kas atļauj sameklēt attēlā iespējamās numura atrašanās vietas, un modificētā Hafa transformācija, kas piemērota tieši numuru slīpuma automātiskai noteikšanai un ir ātrdarbīgāka par klasisko Hafa transformāciju.This paper is an investigation of image analysis methods, required for number plate recognition. A step by step examination of a full recognition cycle is done. Researched methods covers noise filters, locating number plate, detection of plate position and normalization of number plate. Also some ways of recognizing dynamic images are suggested. In context of this work two new methods are introduced – similar neighbor method (for locating number plate) and a modified Hough transform (for detecting position of plate). The modified Hough transform is adapted for number plate recognition and is faster as classical Hough transform