License plate detection using adaptive morphological closing and local adaptive thresholding

Fomani, Babak Abad; Shahbahrami, Asadollah

doi:10.1109/pria.2017.7983035

Cited by 13 publications

(8 citation statements)

References 14 publications

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“…Setelah citra diambil dengan kamera maka biasanya dilakukan proses preprocessing terlebih dahulu, pre-processing bertujuan untuk memperbaiki kualitas sebuah citra digital yang disebabkan oleh noise dalam pengambilan citra. [5] Proses deteksi plat nomor kendaraan: proses ini dilakukan jika citra masukan bukanlah citra plat nomor kendaraan. Artinya sistem mengambil citra yang berupa citra kendaraan kemudian sistem akan mencari lokasi dimana sebuah plat nomor kendaraan berada.…”

Section: Pendahuluanunclassified

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Perancangan Algoritma Optimasi Pada Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Pengolahan Citra

Iman¹,

Syamsuddin²

2020

Komputika

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Pengenalan plat nomor kendaraan khususnya plat nomor Indonesia menggunakan pengolahan citra belum banyak digunakan secara luas. Baru dari pemerintah yang memanfaatkan pengenalan plat nomor kendaraan dengan pengolahan citra sebagai alat otomatis tilang elektronik yang dipasang pada rambu lalu lintas. Beberapa penelitian pengenalan plat nomor dilakukan untuk menghasilakan pengenalan yang terbaik. Pada penelitian ini dibuat sebuah metoda untuk melakukan optimasi pengenalan karakter menggunakan pengolahan citra. Metoda ini menganalisa bentuk kemiripan karakter terhadap karakter utama plat nomor kendaran serta menganalisa dimana posisi karakter tersebut berada. Metoda ini mampu meningkatkan pengenalan karakter plat nomor kendaraan menggunakan pengolahan citra dengan presentase peningkatan akurasi dari 80% menjadi 94%.

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Section: Pendahuluanunclassified

“…Namun jika input citra yang dianalisa adalah citra plat nomor kendaraan maka proses ini dapat dilewati. [5] Proses segmentasi berarti memisahkan karakter pada plat nomor dari latar belakang plat nomor itu sendiri. Proses ini dapat dilakukan dengan mengekstraksi fitur-fitur yang ada pada citra plat nomor, salah satunya adalah kontur citra.…”

Section: Pendahuluanunclassified

Perancangan Algoritma Optimasi Pada Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Pengolahan Citra

Iman¹,

Syamsuddin²

2020

Komputika

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“…In [7], Chang et al suggested a colour-edge-based detector, which focuses on certain edges where the colours match those found in license plates. A more recent approach by Fomani et al, described in [20], relied on a local histogram equalization and simple and adaptive morphological operations. In [6], [13], an initial candidate selection is performed by identifying areas with high density of vertical edges, which are then filtered using rules and constraints on basic geometric properties (aspect ratio, width or height of the candidate boxes).…”

Section: Related Workmentioning

confidence: 99%

Efficient Scale-Adaptive License Plate Detection System

Molina-Moreno

González-Díaz

Díaz-de-María

2019

IEEE Trans. Intell. Transport. Syst.

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License Plate Detection is a common problem in traffic surveillance applications. Although some solutions have been proposed in the literature, their success is usually restricted to very specific scenarios, with their performance dropping in more demanding conditions. One of the main challenges to be addressed for this kind of systems is the varying scale of the license plates, which depends on the distance between the vehicles and the camera. Traditionally, systems have handled this issue by sequentially running single-scale detectors over a pyramid of images. This approach, although simplifies the training process, requires as many evaluations as considered scales, which leads to running times that grow linearly with the number of scales considered. In this paper we propose a scale-adaptive deformable partbased model which, based on a well-known boosting algorithm, automatically models scale during the training phase by selecting the most prominent features at each scale, and notably reduces the test detection time by avoiding the evaluation at different scales. In addition, our method incorporates a empirically constrained-deformation model that adapts to different levels of deformation shown by distinct local features within license plates. As shown in the experimental section, the proposed detector is robust and scale-and perspective-independent, and can work in quite diverse scenarios. Experiments on two datasets show that the proposed method achieves a significantly better performance in comparison with other methods of the state-of-the-art.

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“…In other words, the resolution and model of vehicle cannot be changed when it is applied. Another way is using the dilation is practically interesting because of its property [10]. The main idea of dilation specifies and determines the element of the neighborhood by MATLAB functions as: imdilate(IM, SE) and imdilate(IM, NHOOD).…”

Section: E Vertical and Horizontal Dilationmentioning

confidence: 99%

“…It can be applied in other problem domains license plate (LP) problem. Some works[10][11][12][13][14][15] have given consideration on license plate detection. Generally, their techniques are based on adaptive morphological closing, support vector machine, new zone based and Riesz fractional based model, any of which also need a lot of effort and a long time.…”

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confidence: 99%

License Plate Detection of Myanmar Vehicle Images Captured from the Dissimilar Environmental Conditions

Khin

Phothisonothai

Choomchuay

2017

2017 International Conference on Advanced Computing and Applications (ACOMP)

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Due to the difficulty in defecting the images, in this paper, we proposed the method that can detect region of interest of the license plate for Myanmar vehicles captured from the dissimilar environmental conditions, e.g., different type of license plates, angle of image capturing, and real environmental conditions. In this paper, the horizontal and vertical dilation, skew angle detection and automatic bounding box were proposed to detect the license number from input images. In our experiment, the obtained results showed that an average detection accuracy of 99% which was substantially applied for the license plate detection from the dissimilar environmental conditions.

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License plate detection using adaptive morphological closing and local adaptive thresholding

Cited by 13 publications

References 14 publications

Perancangan Algoritma Optimasi Pada Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Pengolahan Citra

Perancangan Algoritma Optimasi Pada Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Pengolahan Citra

Efficient Scale-Adaptive License Plate Detection System

License Plate Detection of Myanmar Vehicle Images Captured from the Dissimilar Environmental Conditions

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