NEW METHOD FOR HAND GESTURE RECOGNITION USING WAVELET NEURAL NETWORK
الكلمات المفتاحية:
wavelet، multi-wavelet، neural networksالملخص
This paper present a method for hand gesture recognition through Statistic hand gesture which is namely, a subset of American Sign Language (ASL). The proposed technique presents an image of hand gesture by passing it through four stages, preprocessing, normalization, feature extraction, and classification. The wavelet neural network is used to build information models because it can handle very complex interactions. The practical system is simulated using MATLAB. The performance of suggested method is excellent compared with traditional approaches and the final results of selected patterns recognition are powerful.
التنزيلات
Key Dates
منشور
2017-01-01
إصدار
القسم
Articles
الرخصة
هذا العمل مرخص بموجب Creative Commons Attribution 4.0 International License.
The Journal of Engineering and Sustainable Development is an open-access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowed to search, download, share, distribute, print, or link to the full texts of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article.
Creative Commons-Attribution (BY) 
كيفية الاقتباس
NEW METHOD FOR HAND GESTURE RECOGNITION USING WAVELET NEURAL NETWORK. (2017). مجلة الهندسة والتنمية المستدامة, 21(1), 65-73. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/501
