scholarly journals IMPLEMENTASI ALGORITMA YOLO DAN TESSERACT OCR PADA SISTEM DETEKSI PLAT NOMOR OTOMATIS

2022 ◽  
Vol 16 (1) ◽  
pp. 54
Author(s):  
Imam Husni Al amin ◽  
Awan Aprilino
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Detection System ◽  
Extraction Process ◽  
Test Results ◽  
Web Based ◽  
Detection Systems ◽  
Human Labor ◽  
Cross Platform ◽  
Human Effort

Currently, vehicle number plate detection systems in general still use the manual method. This will take a lot of time and human effort. Thus, an automatic vehicle number plate detection system is needed because the number of vehicles that continues to increase will burden human labor. In addition, the methods used for vehicle number plate detection still have low accuracy because they depend on the characteristics of the object being used. This study develops a YOLO-based automatic vehicle number plate detection system. The dataset used is a pretrained YOLOv3 model of 700 data. Then proceed with the number plate text extraction process using the Tesseract Optical Character Recognition (OCR) library and the results obtained will be stored in the database. This system is web-based and API so that it can be used online and on the cross-platform. The test results show that the automatic number plate detection system reaches 100% accuracy with sufficient lighting and a threshold of 0.5 and for the results using the Tesseract library, the detection results are 92.32% where the system is successful in recognizing all characters on the license plates of cars and motorcycles. in the form of Alphanumeric characters of 7-8 characters.

scholarly journals Character Recognition And Extraction of An Indian State License Plates Using K-NN

2019 ◽  
Author(s):  
Rajasekhar Ponakala ◽  
Hari Krishna Adda ◽  
Ch. Aravind Kumar ◽  
Kavya Avula ◽  
K. Anitha Sheela
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Nearest Neighbor ◽  
Extraction Process ◽  
License Plate ◽  
K Nearest Neighbor ◽  
Open Hardware ◽  
Character Extraction ◽  
Indian State ◽  
High Level

License plate recognition is an application-specific optimization in Optical Character Recognition (OCR) software which enables computer systems to read automatically the License Plates of vehicles from digital images. This thesis discusses the character extraction from the respective License Plates of vehicles and problems in the character extraction process. An OCR based training algorithm named k-nearest neighbor with predefined OpenCV libraries is implemented and evaluated in the BeagleBone Black Open Hardware. In an OCR, the character extraction involves certain steps which include Image acquisition, Pre-processing, Feature extraction, Detection/ Segmentation, High-level processing, Decision making. A key advantage of the method is that it is a fairly straightforward technique which utilizes from k-nearest neighbor algorithm segments normalized result as a format in text. The results show that training an image with this algorithm gives better results when compared with other algorithms.

scholarly journals Optical Character Recognition based Webapp

2021 ◽  
Vol 9 (VI) ◽  
pp. 385-389
Author(s):  
Akshay Gharde
Keyword(s):  
Character Recognition ◽  
Web Application ◽  
Optical Character Recognition ◽  
Digital Conversion ◽  
Daily Lives ◽  
Storage And Retrieval ◽  
Optical Character ◽  
Textual Data ◽  
Cross Platform ◽  
Natural Way

As the use of computers in our daily lives increases, so has the need for a natural procedure to interact with the computers. The ultimate aim of human computer interaction is to bring the change that there is always a natural way of interacting with computers coupled with ease and flexibility. Printed and textual media such as prescriptions, invoices, receipts, etc. occupies a large segment of our day-to-day activities and given their volume, it is inefficient to manage them physically as there’s always an associated risk of fading, damage, misplacing, etc. and hence a medium is required for their digital conversion. In this project, we have developed a robust, cross-platform web application that can process the images using PyTesseract based algorithms that can efficiently extract the textual data to facilitate the storage and retrieval of the same. The extracted text can be downloaded as a text file and can also be translated into the desired language. This is an active field of research and thus this paper also discusses various current implementations of the mentioned concept. The Optical Character Recognition framework finds applications in a variety of fields such as business process activities, number plate recognition, KYC and banking processes to name a few.

scholarly journals A Closer Look at Intrusion Detection System for Web Applications

2018 ◽  
Vol 2018 ◽  
pp. 1-27 ◽  
Author(s):  
Nancy Agarwal ◽  
Syed Zeeshan Hussain
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Web Applications ◽  
Detection System ◽  
Web Traffic ◽  
Comprehensive Overview ◽  
Web Based ◽  
Efficient System ◽  
Detection Systems ◽  
Web Attacks

Intrusion Detection System (IDS) acts as a defensive tool to detect the security attacks on the web. IDS is a known methodology for detecting network-based attacks but is still immature in monitoring and identifying web-based application attacks. The objective of this research paper is to present a design methodology for efficient IDS with respect to web applications. In this paper, we present several specific aspects which make it challenging for an IDS to monitor and detect web attacks. The article also provides a comprehensive overview of the existing detection systems exclusively designed to observe web traffic. Furthermore, we identify various dimensions for comparing the IDS from different perspectives based on their design and functionalities. We also propose a conceptual framework of a web IDS with a prevention mechanism to offer systematic guidance for the implementation of the system. We compare its features with five existing detection systems, namely, AppSensor, PHPIDS, ModSecurity, Shadow Daemon, and AQTRONIX WebKnight. This paper will highly facilitate the interest groups with the cutting-edge information to understand the stronger and weaker sections of the domain and provide a firm foundation for developing an intelligent and efficient system.

scholarly journals AN ARCHITECTURE FOR AN INSCRIPTION RECOGNITION SYSTEM FOR SINHALA EPIGRAPHY

2016 ◽  
Vol 4 (12) ◽  
pp. 48-64
Author(s):  
Ruwanmini ◽  
Liyanage ◽  
Karunarathne ◽  
Dias ◽  
Nandasara
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Geographical Location ◽  
Recognition System ◽  
Sri Lankan ◽  
Web Based ◽  
Optical Character ◽  
Scanned Images ◽  
Huge Challenge ◽  
Tracking Module

Sinhala Inscriptions are used as one of the major sources of getting information about ancient Sri Lanka. Revealing the Information from these inscriptions becomes a huge challenge for archeologists. This research paper focused on Sinhala character recognition in ancient Sri Lankan inscription. Our intention is to ease this process by developing a web based application that enable recognition of inscription characters through scanned images and store them in an inscription database.   Using this system people can track geographical location of inscriptions.  Epigraphist could be able to easily obtain Sinhala interpretation of Sri Lankan inscriptions via the optical character recognition feature in our system. Our work on this research project provides benefits to researchers in archaeology field, epigraphists and general public who are interested in this subject.   Inscription site tracking module will present a map that user can go around easily by tracking the locations of inscriptions. This paper presents the Architecture for this Sinhala Epigraphy system.

scholarly journals A Comparative Review on Object Detection System for Visually Impaired

2021 ◽  
Vol 12 (2) ◽  
pp. 1598-1610
Author(s):  
Dr K Sreenivasulu, Et. al.
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Detection System ◽  
Voice Quality ◽  
Natural World ◽  
Blind People ◽  
Visual Disability ◽  
Comparative Review ◽  
Audio Output ◽  
The Voice

Vision is one of the key senses allowing citizens to communicate with the natural world. There are about two hundred million blind people globally and visually disabled people obstruct numerous everyday practices. It is also really critical that blind people recognize their world and realize with which items they communicate. This paper review all the method and tool related to camera-based device to enable the blind person interpret text patterns written on items kept in hand.  This is the system for helping individuals with visual disability interpret and translate text patterns to the audio output. The framework first suggests the approach to take an image from the camera and the area of the target to retrieve the object from the context and derive a text pattern from that object. Diffrent algorithm is assessed in various scenes. The observed text is linked to the blueprint and translated into the performance of the voice. Localized and binarized text patterns utilising Optical Character Recognition (OCR). The text is translated to an audio output. The voice quality is given to theblind person.  

scholarly journals Character Recognition And Extraction of An Indian State License Plates Using K-NN

2019 ◽  
Author(s):  
Rajasekhar Ponakala ◽  
Hari Krishna Adda ◽  
Ch. Aravind Kumar ◽  
Kavya Avula ◽  
K. Anitha Sheela
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Nearest Neighbor ◽  
Extraction Process ◽  
License Plate ◽  
K Nearest Neighbor ◽  
Open Hardware ◽  
Character Extraction ◽  
Indian State ◽  
High Level

License plate recognition is an application-specific optimization in Optical Character Recognition (OCR) software which enables computer systems to read automatically the License Plates of vehicles from digital images. This thesis discusses the character extraction from the respective License Plates of vehicles and problems in the character extraction process. An OCR based training algorithm named k-nearest neighbor with predefined OpenCV libraries is implemented and evaluated in the BeagleBone Black Open Hardware. In an OCR, the character extraction involves certain steps which include Image acquisition, Pre-processing, Feature extraction, Detection/ Segmentation, High-level processing, Decision making. A key advantage of the method is that it is a fairly straightforward technique which utilizes from k-nearest neighbor algorithm segments normalized result as a format in text. The results show that training an image with this algorithm gives better results when compared with other algorithms.

scholarly journals Javanese Character Feature Extraction Based on Shape Energy

2017 ◽  
Vol 5 (1) ◽  
pp. 154-169 ◽  
Author(s):  
Galih Hendra Wibowo ◽  
Riyanto Sigit ◽  
Aliridho Barakbah
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Performance Test ◽  
Test Results ◽  
K Nearest Neighbors ◽  
Method Performance ◽  
Feature Extraction Method ◽  
Character Feature ◽  
Better Than

Javanese character is one of Indonesia's noble culture, especially in Java. However, the number of Javanese people who are able to read the letter has decreased so that there need to be conservation efforts in the form of a system that is able to recognize the characters. One solution to these problem lies in Optical Character Recognition (OCR) studies, where one of its heaviest points lies in feature extraction which is to distinguish each character. Shape Energy is one of feature extraction method with the basic idea of how the character can be distinguished simply through its skeleton. Based on the basic idea, then the development of feature extraction is done based on its components to produce an angular histogram with various variations of multiples angle. Furthermore, the performance test of this method and its basic method is performed in Javanese character dataset, which has been obtained from various images, is 240 data with 19 labels by using K-Nearest Neighbors as its classification method. Performance values were obtained based on the accuracy which is generated through the Cross-Validation process of 80.83% in the angular histogram with an angle of 20 degrees, 23% better than Shape Energy. In addition, other test results show that this method is able to recognize rotated character with the lowest performance value of 86% at 180-degree rotation and the highest performance value of 96.97% at 90-degree rotation. It can be concluded that this method is able to improve the performance of Shape Energy in the form of recognition of Javanese characters as well as robust to the rotation.

scholarly journals MAIL SORTER USING LABVIEW

2012 ◽  
pp. 123-125
Author(s):  
A. NIKHILA ◽  
NISHA A NAIR ◽  
KUMUDA S ◽  
PREETHI K MANE
Keyword(s):  
Code Generation ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
The State ◽  
Labview Software ◽  
The World ◽  
Sorting Process ◽  
Human Effort ◽  
Labview Program ◽  
Real Time Application

The Indian postal system is the largest networks in the world. Being the 7th largest country in the world, major population of the country is rural based, where the basic amenities of life is a sweet dream. In such a scenario, having an efficient mail delivery system is essential. Hence, to eliminate the drawbacks in other processes, we propose to fully automate the sorting process. Unlike the code generation technique, it neither requires any human intervention to generate a code based on the pin code nor will be a problem in case of absence of the pin code. The principle used for sorting is the Optical Character Recognition using LabVIEW software. Camera, placed over the slide unit captures the image of the address. The pin code or the state (in the absence of the pin code) is selected and compared with a set of trained characters in the data base. On finding a positive match, based on the first two digits of the pin code or the first four letters of the state, the mail is segregated by the LabVIEW program involving OCR technique. The processed data is sent to the real time application by the DAQ card, which activates the actuating arm(servo motor) to allow the letters to move to the respective stack(zone) and thus sorting the mails automatically, reducing the human effort and errors.

Development and customization of in-house developed OCR and its evaluation

2018 ◽  
Vol 36 (5) ◽  
pp. 766-781
Author(s):  
Rajeswari S. ◽  
Sai Baba Magapu
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Web Based ◽  
Content Type ◽  
Text Extraction ◽  
Manual Intervention ◽  
Key Phrases ◽  
Microsoft Office ◽  
Read Accuracy ◽  
Scanned Documents

Purpose The purpose of this paper is to develop a text extraction tool for scanned documents that would extract text and build the keywords corpus and key phrases corpus for the document without manual intervention. Design/methodology/approach For text extraction from scanned documents, a Web-based optical character recognition (OCR) tool was developed. OCR is a well-established technology, so to develop the OCR, Microsoft Office document imaging tools were used. To account for the commonly encountered problem of skew being introduced, a method to detect and correct the skew introduced in the scanned documents was developed and integrated with the tool. The OCR tool was customized to build keywords and key phrases corpus for every document. Findings The developed tool was evaluated using a 100 document corpus to test the various properties of OCR. The tool had above 99 per cent word read accuracy for text only image documents. The customization of the OCR was tested with samples of Microfiches, sample of Journal pages from back volumes and samples from newspaper clips and the results are discussed in the summary. The tool was found to be useful for text extraction and processing. Social implications The scanned documents are converted to keywords and key phrases corpus. The tool could be used to build metadata for scanned documents without manual intervention. Originality/value The tool is used to convert unstructured data (in the form of image documents) to structured data (the document is converted into keywords, and key phrases database). In addition, the image document is converted to editable and searchable document.

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