| dc.creator |
Bulugu, Isack |
|
| dc.creator |
Zhijun, Pei |
|
| dc.date |
2016-09-16T12:18:02Z |
|
| dc.date |
2016-09-16T12:18:02Z |
|
| dc.date |
2013-12 |
|
| dc.identifier |
Bulugu, I. and Zhijun, P., An Improved Method for Tanzania Number Plate Location and Segmentation Based on Mathematical Morphology and Regional Features of an Image. |
|
| dc.identifier |
http://hdl.handle.net/20.500.11810/3718 |
|
| dc.description |
In the Automatic Number Plate Recognition System (ANPR), Plate Number Location and Character segmentation are very
important parts of an ANPR system before Recognition part. In this paper, plate number localization and character segmentation using
mathematical morphological approach and regional features of images are discussed from the proposed ANPR system of vehicles in
Tanzania. The proposed algorithm consists of three main modules: Pre-processing (cutting and resizing, convert RGB image to
grayscale image, image binarization use Otsu method), Finding Region of Interest(morphology opening to remove noises & dilation
operation, measure properties of image regions to find candidates), License plate exactly location (finding the LP angle & rotating LP,
cut exactly LP region). The Character segmentation also consist three parts: Eliminate incrimination of the binary using boundary
features, removes impurities using regional features and morphological process, and divide character into sub-images. The results show
an average of 98% successful plate number localization and segmentation for proposed ANPR system in a total of 200 images captured
from a complex outdoor environment in Tanzania. Implementation was done using MATLAB Version 7.11.0 (R2010b). |
|
| dc.language |
en |
|
| dc.publisher |
International Journal of Science and Research |
|
| dc.subject |
Automatic number plate recognition (ANPR) |
|
| dc.subject |
Plate number location |
|
| dc.subject |
Character segmentation |
|
| dc.subject |
MATLAB |
|
| dc.title |
An Improved Method for Tanzania Number Plate Location and Segmentation Based on Mathematical Morphology and Regional Features of an Image |
|
| dc.type |
Journal Article, Peer Reviewed |
|