scholarly journals Pengenalan Plat Nomor Polisi Kendaraan Bermotor

2012 ◽  
Vol 12 (1) ◽  
pp. 35
Author(s):  
Ottopianus Mellolo
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Character Recognition ◽  
Motor Vehicle ◽  
Region Of Interest ◽  
Base Plate ◽  
Character Segmentation ◽  
Test Image ◽  
Average Percentage ◽  
Plate Number

PENGENALAN PLAT NOMOR POLISI KENDARAAN BERMOTOR ABSTRAK Penelitian ini bertujuan membuat sistem yang dapat mengenali karakter pada plat nomor polisi kendaraan yang terdapat pada citra digital. Sampel yang digunakan sebanyak 50 citra uji terdiri atas 25 citra kendaraan pribadi dengan warna dasar plat hitam tulisan putih, 10 citra kendaraan dinas pemerintah dengan warna dasar plat merah tulisan putih, dan  15 citra angkutan umum dengan wara dasar plat kuning tulisan hitam. Adapun Penelitian ini dilakukan melalui beberapa tahap, yaitu (1) Pengolahan Citra, untuk mempersiapkan citra dan mengambil fitur – fitur penting yang akan digunakan pada tahap - tahap selanjutnya (2) Penentuan Region of Interest (ROI) yaitu penentuan posisi plat nomor dalam citra, (3) Segmentasi Karakter yaitu membagi citra plat nomor menjadi citra yang memuat satu karakter, dan (3) pengenalan karakter yaitu mencocokkan karakter yang dicari dengan karakter referensi untuk dikenali. Hasil penelitian menunjukkan bahwa sistem dapat mengenali karakter pada plat nomor polisi kendaraan bermotor untuk ketiga jenis plat nomor dengan persentase rata-rata sebesar 79,43%. Kata kunci: Citra, pengenalan, plat nomor polisi  MOTORIZED VEHICLE POLICE NUMBER PLATE RECOGNITION ABSTRACT` The research is aimed to create one system in recognize the characteristic of the motor vehicle plate number that has digital image. The number of samples used was 50 test image consisted of 25 private vehicle images with written white numbers on the black base plate, 10 govemment vehicle image with written white numbers on the red base plate and 15 public vehicle images with black written numbers on the yellow base plate. The research undenrwent several stages :( 1) Image processing to prepare image and get the important features to be used for next stages (2) Determining Region of Interest (ROl), determining plate position in image, (3) Character segmentation, dividing plate number image which can only accomodate one character ; and (4)Character recognition, character verification that is sought with reference character to be recognized. The results indicatet hat the system can recognize the characters on the motor vehicle police plate number for the three types of the plate numbers with the average percentage 79,43%. Keywords: Image, recognition, police plate number

scholarly journals Experiment-Based Synthetic Structural Analysis Combining Digital Image Processing and a Strong Form Meshfree Method

2020 ◽  
Vol 10 (22) ◽  
pp. 8053 ◽  
Author(s):  
Junwon Park ◽  
Kyeong-Hwan Kim ◽  
Young-Cheol Yoon ◽  
Sang-Ho Lee
Keyword(s):  
Image Processing ◽  
Structural Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
Region Of Interest ◽  
Meshfree Method ◽  
Strong Form ◽  
Bending Test ◽  
Target Area ◽  
Tracking Point

This paper presents an experiment-based synthetic structural analysis method that combines digital image processing (DIP) and the particle difference method (PDM), which is a strong form-based meshfree method. The proposed method uses images to determine the displacement of deformed specimens, interpolates the displacement onto nodes of the PDM model without meshes or grids, and calculates the kinematic variables. Furthermore, the pixel extraction method for the target area and the method of setting the region of interest for expediting DIP were used during the synthetic structural analysis. A method for effectively expanding the number of tracking points and an improved method for labeling tracking points are also presented. To verify the performance of the analysis, the experimental and numerical analysis results of a three-point bending test on a rubber beam were compared in terms of various mechanical variables as well as with the PDM results of a simulated bending test. It was found that tracking point expansion and adjusting the radius of the domain of influence are advantageous for performing an accurate calculation without losing computational efficiency. It was demonstrated that the synthetic structural analysis effectively overcomes the shortcomings of the conventional experiments and the limitations of pure simulations.

The License Plate Recognition Technology Based on Digital Image Processing

2011 ◽  
Vol 267 ◽  
pp. 778-782 ◽  
Author(s):  
Juan Hua Zhu ◽  
Ang Wu ◽  
Juan Fang Zhu
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Convenient Method ◽  
Search Algorithm ◽  
Character Segmentation ◽  
Scale Transformation ◽  
License Plate ◽  
License Plate Recognition ◽  
Region Search

A rapid and convenient method of license plate recognition is discussed. The color plates are preprocessed by transform gray-scale transformation and image enhancement. The license plate is located by edge detection and region search algorithm, and the character segmentation is made by projection. Finally, the template is matched, and the license plate number is recognized quickly and accurately. The experiment shows that the method used in this paper can achieve better recognition results.

scholarly journals Automated detection of vehicles license plate using image processing techniques

2020 ◽  
Vol 18 (3) ◽  
pp. 1408
Author(s):  
Farhana Ahmad Poad ◽  
Noor Shuraya Othman ◽  
Roshayati Yahya Atan ◽  
Jusrorizal Fadly Jusoh ◽  
Mumtaz Anwar Hussin
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Region Of Interest ◽  
Automated Detection ◽  
License Plate ◽  
Image Processing Techniques ◽  
Individual Character ◽  
Split And Merge ◽  
Processing Techniques

The aim of this project is to design an Automated Detection of License Plate (ADLP) system based on image processing techniques. There are two techniques that are commonly used in detecting the target, which are the Optical Character Recognition (OCR) and the split and merge segmentation. Basically, the OCR technique performs the operation using individual character of the license plate with alphanumeri characteristic. While, the split and merge segmentation technique split the image of captured plate into a region of interest. These two techniques are utilized and implemented using MATLAB software and the performance of detection is tested on the image and a comparison is done between both techniques. The results show that both techniques can perform well for license plate with some error.

Study of Various Image Segmentation Methodologies

2017 ◽  
pp. 1-27
Author(s):  
Abahan Sarkar ◽  
Ram Kumar
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
New Technologies ◽  
Region Of Interest ◽  
Literature Survey ◽  
Segmentation Algorithms ◽  
Segmentation Image

In day-to-day life, new technologies are emerging in the field of Image processing, especially in the domain of segmentation. Image segmentation is the most important part in digital image processing. Segmentation is nothing but a portion of any image and object. In image segmentation, the digital image is divided into multiple set of pixels. Image segmentation is generally required to cut out region of interest (ROI) from an image. Currently there are many different algorithms available for image segmentation. This chapter presents a brief outline of some of the most common segmentation techniques (e.g. Segmentation based on thresholding, Model based segmentation, Segmentation based on edge detection, Segmentation based on clustering, etc.,) mentioning its advantages as well as the drawbacks. The Matlab simulated results of different available image segmentation techniques are also given for better understanding of image segmentation. Simply, different image segmentation algorithms with their prospects are reviewed in this chapter to reduce the time of literature survey of the future researchers.

scholarly journals Vehicle Number Plate Recognition using Micro Processor

2019 ◽  
Vol 8 (12) ◽  
pp. 3682-3684
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition System ◽  
Processing Technology ◽  
License Plate ◽  
Text Format ◽  
Optical Character ◽  
Plate Number ◽  
Image Processing Technology

An automatic license number plate recognition system that uses image processing technology for identifying the written characters and numbers on the vehicle’ license plate. The system can be used in highly secured areas to provide more safety, and can be used in parking, traffic, and other places to monitor all vehicle’s number plate in a predefined area. The character is recognized by the OCR technology that is optical character recognition system. It generates the vehicle’s license plate number in a text format. The recognized number from the license plate then can be used to retrieve more information about the vehicle and the owner.

scholarly journals Algorithm for determining the angular position of the ship’s deck from an unmanned aircraft using digital image processing

2020 ◽  
Vol 30 (4) ◽  
pp. 87-97
Author(s):  
A. A. Makarenko
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Angular Position ◽  
Landing Site ◽  
Unmanned Aircraft ◽  
Test Results ◽  
Test Image ◽  
Automatic Landing ◽  
Inclination Angles

Problem statement. An unmanned vertical take-off and landing aircraft equipped with means for analyzing parameters of a certain pattern is usually not able to land on a landing site that is not equipped with the appropriate markings. To solve this problem, it is possible to install onboard the UMA means for generating a special test image that is projected from the aircraft to the intended landing site, and means for automatically measuring and analyzing the parameters of this image.Objective. Develop an algorithm for applying digital image processing to determine the angular position of the ship’s deck or any other flat landing ground from an unmanned aircraft with vertical take-off and landing. The article presents the calculated relations that allow calculating the angular position and evaluating the general condition of the landing ground using a 3D model of its surface.Results. An algorithm has been developed according to which a particular test image is generated by a group of laser emitters on the landing site. Digital image processing methods are used to analyze the test image to assess the condition and determine the inclination angles of the landing site.Practical implications. The test results of the considered algorithm showed the possibility of its application in the system of automatic landing of an unmanned aircraft with vertical take-off and landing.

scholarly journals Advanced car-parking security platform using Arduino along with automatic license and number recognition

2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Bafreen Najeb Mohammed ◽  
Hawar B. Ahmad
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Development Platform ◽  
Number Recognition ◽  
Open Source Hardware

The open-source hardware development platform Arduino has been growing in recent years. Nowadays, the Arduino platform became one of the important parts in remote control and monitor of electrical devices. This paper aims to propose an application of digital image processing along with Arduino, which can be useful in car-parking place to be more secure. Arduino will detect the car and take a picture for its plat and send it to the system. Then, system applies digital image processing technique in the image. Different algorithms are incorporated in system such as segmentation, normalization, localization, orientation and optical character recognition (OCR) which analyze certain features in image and predicts car plate numbers. Afterwards the resulting data are compared against records in a stored database.

scholarly journals Proposal for Automatic Vehicle Number Plate Recognition System in POLIMAS

2020 ◽  
Vol 4 (1) ◽  
pp. 20-27
Author(s):  
Keyword(s):  
Edge Detection ◽  
Traffic Control ◽  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
Character Segmentation ◽  
Identification System ◽  
Recognition Mechanism ◽  
Detection Techniques ◽  
Plate Number

Automatic Vehicle Number Plate Recognition (AVNPR) system is an image processing technology in computer vision which captures the image of the vehicle and recognizes its number plate. Currently, the security and management of transportation system becomes an important key in controlled place such as campus area. With an increased number of vehicles, there is a need for vehicle recognition mechanism that is effective, affordable and efficient. The objective of this paper is to propose an efficient automatic vehicle identification system by recognizing the vehicle plate number. The system will be installed at the main entrance of POLIMAS to ensure that only the authorized vehicles can automatically enter the campus area. Once the vehicle is detected by the input sensors, AVNPR system will capture the image of vehicle plate number. An image is then extracted and investigated character segmentation by using optical character recognition (OCR). The method used for detection of a plate number is by pre-processing of the image and using a combination of Sobel edge detection and Laplacian edge detection techniques. Bounding Box technique is used to find the number plate and character segmentation. For character recognition, OCR method is used by using template matching to compare the segmented image with the template. The system is sustainable as the camera will only be switched on when a car is present. The propose system successfully detects and recognizes the vehicle number plate on real images. This system can also be used for security and traffic control.

scholarly journals CHARACTER IMAGE SEGMENTATION OF JAVANESE SCRIPT USING CONNECTED COMPONENT METHOD

2019 ◽  
Vol 12 (2) ◽  
pp. 67
Author(s):  
Yuna Sugianela ◽  
Nanik Suciati
Keyword(s):  
Image Segmentation ◽  
Character Recognition ◽  
Region Of Interest ◽  
Character Segmentation ◽  
Translation System ◽  
Important Process ◽  
Connected Component ◽  
Projection Profile ◽  
Centroid Distance ◽  
Meaningful Word

Automation of Javanese script translation is needed to make it easier for people to understand the meaning of ancient Javanese script. By using Javanese script image as input, the translation system generally consists of character segmentation, character recognition, and combining the recognized characters as a meaningful word. The segmentation which obtains region of interest of each character, is an important process in the translation system. In the previous research, segmentation using projection profile method can separate each character well. The method can overcome characters overlapping, but it still produces truncated characters. In this study, we proposed a new segmentation to reduce the truncated character. The first step of the proposed method is pre-processing that consists of converting input into binary image and cleaning noises. The next step is to determine the connected component labels, which further perform as candidate of characters. Some of the candidates are still represented by more than one labels, so that we need a process to merge the connected component labels that have centroid distance less than threshold. We evaluate the proposed method using Intersection over Union (IoU). The evaluation shows the best accuracy 93,26%.

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

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