Finger gesture recognition using HTK toolkit
Also available in printed version : QA76.9.H85 S93 2012 raf
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Bachelor thesis |
| 語言: | 英语 |
| 出版: |
Universiti Teknologi Malaysia
2025
|
| 主題: | |
| 在線閱讀: | https://utmik.utm.my/handle/123456789/60493 |
| Abstract | Abstract here |
| _version_ | 1854975092679770112 |
|---|---|
| author | Syakira Hana Ahmad Khairi |
| author2 | Eko Supriyanto, supervisor |
| author_facet | Eko Supriyanto, supervisor Syakira Hana Ahmad Khairi |
| author_sort | Syakira Hana Ahmad Khairi |
| description | Also available in printed version : QA76.9.H85 S93 2012 raf |
| format | Bachelor thesis |
| id | utm-123456789-60493 |
| institution | Universiti Teknologi Malaysia |
| language | English |
| publishDate | 2025 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| record_pdf | Abstract |
| spelling | utm-123456789-604932025-08-21T07:37:47Z Finger gesture recognition using HTK toolkit Syakira Hana Ahmad Khairi Eko Supriyanto, supervisor Human-computer interaction Human-machine systems Also available in printed version : QA76.9.H85 S93 2012 raf Human computer interface (HCI) has been in existence since 1980, and until today, it has become more sophisticated and advanced. Gesture is one of HCI method, is still under ongoing research try to apply the full body motion signal as a medium of interaction with machines or computers. In addition, most electronic devices are also becoming cheaper and affordable to everyone, so the desire to produce a matrix-style high-tech generation is possible in the years to come. Based on such enlightenment, finger gesture recognition is proposed in this project using Hidden Markov Models Kit (HTK). Five of the six-finger gestures have been developed. For the evaluation, some tests were made using parameters such as number of sensors, number of participants involved, and the number of signals used which rely solely on users. The system achieved a precision of 100% for individual users and 77.78% for seven people. Therefore, it can be concluded that, finger gesture recognition system is more suitable for use as an individual and is not suitable for public utilization atiff UTM 84 p. Project Paper (Sarjana Muda Kejuruteraan (Bio - Perubatan)) - Universiti Teknologi Malaysia, 2012 2025-03-17T06:40:34Z 2025-03-17T06:40:34Z 2012 Bachelor thesis https://utmik.utm.my/handle/123456789/60493 valet-20171012-094858 vital:104432 ENG Closed Access UTM Complete Unpublished application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Human-computer interaction Human-machine systems Syakira Hana Ahmad Khairi Finger gesture recognition using HTK toolkit |
| thesis_level | Other |
| title | Finger gesture recognition using HTK toolkit |
| title_full | Finger gesture recognition using HTK toolkit |
| title_fullStr | Finger gesture recognition using HTK toolkit |
| title_full_unstemmed | Finger gesture recognition using HTK toolkit |
| title_short | Finger gesture recognition using HTK toolkit |
| title_sort | finger gesture recognition using htk toolkit |
| topic | Human-computer interaction Human-machine systems |
| url | https://utmik.utm.my/handle/123456789/60493 |
| work_keys_str_mv | AT syakirahanaahmadkhairi fingergesturerecognitionusinghtktoolkit |