Plate Detection and Recognition of Iraqi License Plate Using KNN Algorithm

Alaidi, Abdul Hadi M.; Alsaidi, Saif Ali Abd Alradha; Yahya, Omar

doi:10.31185/eduj.vol1.iss26.102

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…Support Vector Machine (SVM) is saddled with the responsibility of finding a hyperplane or set of hyperplanes within an N-dimensional space, where N is the number of features, to divide the data points into distinct classes [44][45][46][47]. The distance between data points belonging to different classes is maximized by the optimal hyperplane.…”

Section: Linear Support Vector Classifier (Linear Svc)mentioning

confidence: 99%

Dark Web Illegal Activities Crawling and Classifying Using Data Mining Techniques

Alaidi

Al_airaji

Alrikabi

et al. 2022

Int. J. Interact. Mob. Technol.

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Dark web is a canopy concept that denotes any kind of illicit activities carried out by anonymous persons or organizations, thereby making it difficult to trace. The illicit content on the dark web is constantly updated and changed. The collection and classification of such illegal activities are challenging tasks, as they are difficult and time-consuming. This problem has in recent times emerged as an issue that requires quick attention from both the industry and academia. To this end, efforts have been made in this article a crawler that is capable of collecting dark web pages, cleaning them, and saving them in a document database, is proposed. The crawler carries out an automatic classification of the gathered web pages into five classes. The classifiers used in classifying the pages include Linear Support Vector Classifier (SVC), Naïve Bayes (NB), and Document Frequency (TF-IDF). The experimental results revealed that an accuracy rate of 92% and 81% were achieved by SVC and NB, respectively.

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Section: Linear Support Vector Classifier (Linear Svc)mentioning

confidence: 99%

Dark Web Illegal Activities Crawling and Classifying Using Data Mining Techniques

Alaidi

Al_airaji

Alrikabi

et al. 2022

Int. J. Interact. Mob. Technol.

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“…Since license plates are different and specific for every country, there is a wide range of algorithms that can be used depending on the license plate design [6]. In Iraq, there are two main license plate styles [7], [8], which are the old style in Figure 1(a) and the newest style in Figure 1(b), and both are still used. The old-style contains Eastern Arabic numerals and Arabic characters, and the newest style contains Arabic numerals, Eastern Arabic numerals, Arabic characters, and English characters.…”

Section: Introductionmentioning

confidence: 99%

Accurate license plate recognition system for different styles of Iraqi license plates

Altyar¹,

Hussein

Tawfeeq

2023

Bulletin EEI

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Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recognize all these license plate types using the same algorithm. In this work, a new method has been proposed to efficiently recognize all these types of license plates. This has been done by utilizing a series of algorithms for preprocessing and recognition with new identification strategies. The results show that the system recognized license plate numbers with higher accuracy, reaching up to 97.85%. However, the method field to detect license plates when there are some high deformations in plate numbers or when they are partially covered with mud, which makes it difficult to distinguish numbers.

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