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Gaussian Fitting Model for Non-Geometric Features in Gesture Recognition System: Analysis Study

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Mokhtar M. Hasan

Mokhtar M Hasan. Gaussian Fitting Model for Non-Geometric Features in Gesture Recognition System: Analysis Study. International Journal of Computer Applications 148(9):39-41, August 2016. BibTeX

	author = {Mokhtar M. Hasan},
	title = {Gaussian Fitting Model for Non-Geometric Features in Gesture Recognition System: Analysis Study},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2016},
	volume = {148},
	number = {9},
	month = {Aug},
	year = {2016},
	issn = {0975-8887},
	pages = {39-41},
	numpages = {3},
	url = {},
	doi = {10.5120/ijca2016911332},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Gesture language is considered as secondary language for most of people and main language for hearing impaired people, it is considered as international non-spoken language that make the understanding between different tongues possible regardless which country is this, it is also considered the first language that can be act for children in which they express they need in a movement.

There are vast range of non-geometric features that can applied to recognize specific object, we have applied in this paper novel algorithm by building Gaussian model that covers the area of the hand gesture which may or may not circular area, because of that Gaussian is chosen for any circular or oval shape depending on the presented gesture itself, furthermore, rotation variation has been solved in order to reduce the database size used for training the model, experimental results show a promising outcomes that dominant on the other non-geometric techniques.


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Gesture recognition system, Gaussian classifier, Gaussian model, non-geometric features