A Design Flow for Robust License Plate Localization and Recognition in Complex Scenes

Abstract

In this paper, we present a new design flow for robust license plate localization and recognition. The algorithm consists of three stages: 1) license plate localization; 2) character segmentation; and 3) feature extraction and character recognition. The algorithm uses Mexican hat operator for edge detection and Euler number of a binary image for identifying the license plate region. A pre-processing step using median filter and contrast enhancement is employed to improve the character segmentation performance in case of low resolution and blur images. A unique feature vector comprised of region properties, projection data and reflection symmetry coefficient has been proposed. Back propagation artificial neural network classifier has been used to train and test the neural network based on the extracted feature. A thorough testing of algorithm is performed on a database with varying test cases in terms of illumination and different plate conditions. Practical considerations like existence of another text block in an image, presence of dirt or shadow on or near license plate region, license plate with rows of characters and sensitivity to license plate dimensions have been addressed. The results are encouraging with success rate of 98.10% for license plate localization and 97.05% for character recognition

A Survey on Automatic License Plate Extraction Methods

“…After detecting the edges in the image, the required area is then evaluated based on the geometrical features such as the ratio of width and height, size and orientation. In [10] Mexican hat operator is used to detect the edges which perform smoothing before extracting edges. It is very easy and straightforward but accurate pre-processing is needed…”

A New Method for Automatic Vehicle License Plate Detection

“…Após o reconhecimento, é necessário segmentar os dígitos da placa para posterior classificação. Nesta etapa do processamento, diversos métodos são utilizados, tais como transformada de Gabor e quantização vetorial [6], combinações de morfologia matemática [7] [8]. Diante do exposto, este trabalho propõe uma metodologia para realizar a detecção de placas de licenciamento veicular, segmentação e classificação dos dígitos contidos nas placas.…”

Variance Window Based Car License Plate Localization

“…Usually, color based methods are memory-consuming and unsuitable for real time applications due to large data processing, and sensitivity to illumination variations [13].…”