Exploring  the traffic sign recognition problem

dc.contributor.advisor	Halawani, Alaa
dc.contributor.author	Talahmeh, Ala
dc.contributor.author	Amro, Asma
dc.contributor.author	Mansour, Dua
dc.date.accessioned	2022-03-28T06:05:57Z
dc.date.accessioned	2022-05-22T08:16:38Z
dc.date.available	2022-03-28T06:05:57Z
dc.date.available	2022-05-22T08:16:38Z
dc.date.issued	2009-06-01
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/7663
dc.description	no of pages 62, 22889, تكنولوجيا المعلومات 6/2009 , in the store
dc.description.abstract	In this project a technique suggested as a solution for traffic sign recognition is presented. Scale-Invariant Feature Transform (SIFT) was examined to perform recognition (Detection and Classification). SIFT proved to be excellent in the detection and classification of traffic signs. Since SIFT is orientation invariant, orientation histogram used to make the feature orientation dependent. We used two databases of traffic signs images for testing the system, the result showed a success rate of (96.67%).	en_US
dc.language.iso	en	en_US
dc.publisher	جامعة بوليتكنك فلسطين - تكنولوجيا المعلومات	en_US
dc.subject	the traffic sign	en_US
dc.title	Exploring the traffic sign recognition problem	en_US
dc.type	Other	en_US