Holographic vision system based on non-diffractive optical scanning holography and deep learning
Research output: Conference Papers › RGC 31A - Invited conference paper (refereed items) › Yes › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Publication status | Published - 18 Nov 2019 |
Conference
| Title | SPIE/COS Photonics Asia 2019 |
|---|---|
| Location | Hangzhou International Expo Center |
| Place | China |
| City | Hangzhou |
| Period | 20 - 23 October 2019 |
Link(s)
Abstract
We proposed a holographic vision system (HVS) based on a hologram acquisition and a hologram classification units, for capturing and identifying holograms of deformable objects. Non-diffractive optical scanning holography (ND-OSH) is used to capture holograms of physical objects, and a deep learning classifier is applied to deduce the identity of the hologram. Our proposed HVS is evaluated with the set of handwritten numerals. Experimental results reveal that with our proposed HVS, holograms of the test samples can be captured, and subsequently classified with accuracy of over 99.5%.
Research Area(s)
- Convolutional neural network, Deep learning, Hologram classification, Non-diffractive optical scanning holography, Optical Scanning holography
Bibliographic Note
Research Unit(s) information for this publication is provided by the author(s) concerned.
Citation Format(s)
Holographic vision system based on non-diffractive optical scanning holography and deep learning. / Tsang, Peter W. M.; Lam, H.
2019. SPIE/COS Photonics Asia 2019, Hangzhou, China.
2019. SPIE/COS Photonics Asia 2019, Hangzhou, China.
Research output: Conference Papers › RGC 31A - Invited conference paper (refereed items) › Yes › peer-review
