Lip Movement Recognition using Histogram of Oriented Gradient (HOG) and Support Machine Vector (SVM) for Arabic Word
DOI:
https://doi.org/10.33022/ijcs.v12i6.3596Kata Kunci:
Visual speech recognition, Lip-reading, Modern Standard Arabic, HOG Feature Extraction, SVM ClassificationAbstrak
This research aims to develop a lip gesture recognition system in Arabic words by utilizing Histogram of Oriented Gradient (HOG) feature extraction and Support Vector Machine (SVM) classification. The evaluation was conducted on a dataset of 1749 videos with male and female participation using Modern Standard Arabic. The 10 cross-fold validation method was used to measure the performance of the system. By applying a polynomial kernel, this study achieved an accuracy rate of 95.63%, while the word recognition rate reached 96%. These results confirm the system's ability to recognize lip movements with precision, confirming the effectiveness of the approach used in visual recognition for Arabic.
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Hak Cipta (c) 2023 Fahmi Muhammad Rabbani Rabbani, Bima Sena Bayu Dewantara, Endra Pitowarno
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.