文章基本信息

标题：Classification of Hand Gestures Using Gabor Filter with Bayesian and Naïve Bayes Classifier
本地全文：下载
作者：Tahira Ashfaq ; Khurram Khurshid
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：3
DOI：10.14569/IJACSA.2016.070340
出版社：Science and Information Society (SAI)
摘要：A hand Gesture is basically the movement, position or posture of hand used extensively in our daily lives as part of non-verbal communication. A lot of research is being carried out to classify hand gestures in videos as well as images for various applications. The primary objective of this communication is to present an effective system that can classify various static hand gestures in complex background environment. The system is based on hand region localized using a combination of morphological operations. Gabor filter is applied to the extracted region of interest (ROI) for extraction of hand features that are then fed to Bayesian and Naïve Bayes classifiers. The results of the system are very encouraging with an average accuracy of over 90%.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Human Computer Interaction; Hand Segmentation; Gesture recognition; Gabor Filter; Bayesian and Naïve Bayes classifiers; Feature Extraction; Image Processing