An Enhanced Method for Detecting the Shaded Images of the Car License Plates based on Histogram Equalization and Probabilities
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 10
Abstract
Shadow is one of the major and significant challenges in detection algorithms which track the objects such as the license plates. The quality of images captured by cameras is influenced by weather conditions, low ambient light and low resolution of the camera. The shadow in images reduces the reliability of the sight algorithms of the device as well as the visual quality of images. The previous papers indicate that no effective method has been presented to improve the license plate detection accuracy of the shaded images. In other words, the methods that have been presented for automatic license plate detection in shadowed images until now use a combination of color features and texture of the image. In all these methods, in order to detect the frame of the shadow and the texture of the image, sufficient light is required in the image; this necessity cannot be found in most of the regular images captured by road cameras. In order to solve this problem, an improved license plate detection method is presented in this research which is able to detect the license plate area in shadowed images effectively. In fact, this is a contrast-improving method which utilizes the dual binary method for automatic plate detection and is introduced to analyze the interior images with low contrast, and also night shots, blurred and shadowed images. In this method, the histogram of the image is firstly calculated for each dimension and then the probability of each pixel in the whole image is obtained. As a result, after calculating the cumulative distribution of the pixels and replacing it in the image, it will be possible to remove the shadow from the image easily. This new method of detection was tested and simulated for 1000 images of vehicles under different conditions. The results indicated the detection accuracy of 90/30, 97/87 and 98/70 percent for the license plates detection in three databases of University of Zagreb, Numberplates.com and National Technical University of Athens, respectively. In other words, comparing the performance of the proposed method with two similar and new methods, namely Hommos and Azam, indicates an average improvement of 26/70 and 72/95 percent for the plate detection and 32/38 and 36/53 percent for the time required for rapid and correct license plate detection, even in shaded images.
Authors and Affiliations
Mohammad Faghedi, Behrang Barekatain, Kaamran Raahemifar
Keywords
Related Articles
- EP ID EP408218
- DOI 10.14569/IJACSA.2018.091056
- Views 94
- Downloads 0
Programming Technologies for the Development of Web-Based Platform for Digital Psychological Tools
The choice of the tools and programming technologies for information systems creation is relevant. For every projected system, it is necessary to define a number of criteria for development environment, used libraries an...
The Impact of Knowledge Management on Organizational Performance
In today’s business, knowledge is considered as a core asset in any organization, even it can be considered as important as technological capital. It is part of human abilities and thus human capital. Knowledge managemen...
E-Assessment System Based on IMS QTI for the Arabic Grammar
Nowadays e-learning has become a fundamental stream of learning. E-assessment is an important and essential phase of the e-learning process because of all the decisions we will make about learners when teaching them. In...
Detection Capability and CFAR Loss Under Fluctuating Targets of Different Swerling Model for Various Gamma Parameters in RADAR
Target detection of RADAR deals with different and manifold problems over few decades. The detection capability is one of the most significant factors in RADAR system. The main aim of detection is to increase probability...
A New Approach for Leukemia Identification based on Cepstral Analysis and Wavelet Transform
This paper implements a new leukemia identification method which depends on Mel frequency cepstral coefficient (MFCC) feature extraction and wavelet transform. Leukemia identification is a measurement of blood cell featu...