Object detection and recognition are crucial in the field of computer vision an active area research. However, actual object processes, accuracy is often degraded due to resolution mismatches between training test image data. To solve this problem, we designed developed integrated super-resolution framework by proposing technique that improves accuracy. In detail, collected a number license pla...

License plate detection (LPD) is one of the most important aspects of an automatic license plate recognition system. Although there have been some successful license plate recognition (LPR) methods in past decades, it is still a challenging problem because of the diversity of plate formats and outdoor illumination conditions in image acquisition. Because the accurate detection of license plates...

This thesis is to present a new approach for license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and Artificial neural Network. This thesis consists of three main parts. The first part is to locate and extract the license-plate in an image. The second part is to train of the license-plate. The third part is to real time scan recognize of the license-plate. Traditional lice...

In a vehicle license plate recognition system, tilt vehicle license plate has a bad effect on its character segmentation and recognition. In this paper, tilt models of a plate are analyzed and a approach for number plate tilt correction is presented. Hough Transformation is an effective method to obtain vertical or horizontal angle. Though rotating a correct angle, Tilt vehicle license will be ...

In order to accurately detect the various sizes of vehicle license plates which are included in input image, we introduce hierarchical approach and overlapped partitioning technique in this paper. The proposed approach firstly attempts the license plate detection for entire image. If detection is failed, the image is partitioned into 3 overlapped rectangular areas and the license plate detectio...