Improved license plate detection using HOG-based features and genetic algorithm

dc.contributor	MUHAMMAD, Jawad
dc.contributor	ALTUN, Halis
dc.date.accessioned	2020-08-07T12:56:45Z
dc.date.available	2020-08-07T12:56:45Z
dc.date.issued	2016
dc.identifier	10.1109/SIU.2016.7495978
dc.identifier.issn	9781509016792 (ISBN)
dc.identifier.uri	http://hdl.handle.net/20.500.12498/3013
dc.description.abstract	In this paper, a new improved plate detection method which uses genetic algorithm (GA) is proposed. GA randomly scans an input image using a fixed detection window repeatedly, until a region with the highest evaluation score is obtained. The performance of the genetic algorithm is evaluated based on the area coverage of pixels in an input image. It was found that the GA can cover up to 90% of the input image in just less than an average of 50 iterations using 30×130 detection window size, with 20 population members per iteration. Furthermore, the algorithm was tested on a database that contains 1537 car images. Out of these images, more than 98% of the plates were successfully detected. © 2016 IEEE.
dc.language.iso	Turkish
dc.publisher	Institute of Electrical and Electronics Engineers Inc.
dc.source	24th Signal Processing and Communication Application Conference, SIU 2016
dc.subject	License Plate Detection
dc.subject	HOG
dc.subject	Genetic Algorithm
dc.title	Improved license plate detection using HOG-based features and genetic algorithm
dc.type	Konferans Bildirisi