Automatic Number Plate Recognition System Using Improved Segmentation Method

Patel, Bhavin; Singhadia, Ashish

doi:10.14445/22315381/ijett-v16p277

Cited by 1 publication

(3 citation statements)

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“…Images captured from a video camera are processed though a software which facilitates ANPR. The License Plate Recognition (LPR) system operates in four major steps, as given below [5,6]:…”

Section: A Backgroundmentioning

confidence: 99%

“…This is the beginning phase in a LPRS which is obtained by an acquisition technique for image [7]. A high resolution digital camera is employed to acquire the input vehicle image which can be captured from distance of 4-5 meters of vehicle from the acquisition system [6]. One can also use a video camera for capturing of this beginning image.…”

Section: A Backgroundmentioning

confidence: 99%

“…It is also known as the Character Separation wherein one has to find characters in the license plate image and recognize them properly [6]. In the segmentation, the license plate image is converted into binary image and thereafter characters are divided into segments of essential parts to obtain the characters separately [9].…”

Section: (Iii) License Plate Segmentationmentioning

confidence: 99%

See 2 more Smart Citations

Feasibility of Efficient Number Plate Recognition using Morphological Dilation and Support Vector Machine

Vaishnav¹,

Ahuja²,

Mandot³

2019

IJRTE

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Intelligent data acquisition of vehicle number plate plays a significant role to recognize a vehicle and it automatic parking, traffic movement and scheduling, tracking of stolen vehicle, and many more. Although different methodologies of automatic number plate reading have developed alongwith their algorithms, still an efficient number plate recognition technique for better segmentation and recognition of the captured number plate using Morphological Dilation and Support Vector Machine (SVM) are expected to be helpful. In this paper, we present a modified method for recognition of contents of number plate using morphological dilation and SVM. We have compared our results with those from the existing models using Wavelet Transform and Artificial Neural Network techniques. Superiority of present methodology is established using parameters like image segmentation and recognition.

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“…Images captured from a video camera are processed though a software which facilitates ANPR. The License Plate Recognition (LPR) system operates in four major steps, as given below [5,6]:…”

Section: A Backgroundmentioning

confidence: 99%

Section: A Backgroundmentioning

confidence: 99%