Segmentation-free Word Spotting for Handwritten Arabic Documents

dc.contributor.author	Khaissidi, Ghizlane
dc.contributor.author	Elfakir, Youssef
dc.contributor.author	Mrabti, Mostafa
dc.contributor.author	El Yacoubi, Mounîm
dc.contributor.author	Chenouni, Driss
dc.date	2016-09
dc.date.accessioned	2021-07-07T09:18:45Z
dc.date.available	2021-07-07T09:18:45Z
dc.identifier.issn	1989-1660
dc.identifier.uri	https://reunir.unir.net/handle/123456789/11565
dc.description.abstract	In this paper we present an unsupervised segmentation-free method for spotting and searching query, especially, for images documents in handwritten Arabic, for this, Histograms of Oriented Gradients (HOGs) are used as the feature vectors to represent the query and documents image. Then, we compress the descriptors with the product quantization method. Finally, a better representation of the query is obtained by using the Support Vector Machines (SVM).	es_ES
dc.language.iso	eng	es_ES
dc.publisher	International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)	es_ES
dc.relation.ispartofseries	;vol. 4, nº 1
dc.relation.uri	https://ijimai.org/journal/bibcite/reference/2519	es_ES
dc.rights	openAccess	es_ES
dc.subject	classification	es_ES
dc.subject	image recognition	es_ES
dc.subject	HOG	es_ES
dc.subject	arabic documents	es_ES
dc.subject	word spotting	es_ES
dc.subject	IJIMAI	es_ES
dc.title	Segmentation-free Word Spotting for Handwritten Arabic Documents	es_ES
dc.type	article	es_ES
reunir.tag	~IJIMAI	es_ES
dc.identifier.doi	http://doi.org/10.9781/ijimai.2016.411

Ítems relacionados