Philippine vehicle plate localization using image thresholding and genetic algorithm
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
IEEE Region 10 Annual International Conference, Proceedings/TENCON
First Page
2822
Last Page
2825
Publication Date
2-8-2017
Abstract
This paper proposes a vehicle plate localization method using genetic algorithm integrated with image thresholding. Image thresholding outputs a value which varies on the time the image is captured. Genetic algorithm on the other hand, executed the license plate region detection of the digital image which depends on the set-level of the image threshold values obtained. Using the proposed algorithm, it was shown how the algorithm was effective on finding the plate location in a given image. Results show that the different parameters tested were successful and converges to a point where the plate locations can be located. The algorithms were tested on an image of a vehicle equipped with a license plate on its frontal view tested on a large number of trials. The genetic algorithm initialized 2000 chromosomes as its initial population and a fixed generation's count of 100. It was observed that the time it took for the program to locate the plate is about 3 seconds. Another finding observed is that by varying the initial chromosome count and generation count will lead to longer computation time with increased accuracy. On the contrary, if the initial values were lessened, computation time will be less but the accuracy lessen. Results show that this plate localization technique successfully locates the plate and may be calibrated depending on the time of analysis. © 2016 IEEE.
html
Digitial Object Identifier (DOI)
10.1109/TENCON.2016.7848557
Recommended Citation
Bedruz, R., Sybingco, E., Bandala, A. A., Quiros, A., Uy, A. P., & Dadios, E. P. (2017). Philippine vehicle plate localization using image thresholding and genetic algorithm. IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2822-2825. https://doi.org/10.1109/TENCON.2016.7848557
Disciplines
Manufacturing
Keywords
Vehicle detectors; Genetic algorithms; Image processing
Upload File
wf_yes