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Logarithmic r-[theta] mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes
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posted on 2023-06-08, 09:22 authored by Ioannis Kypraios, Rupert YoungRupert Young, Chris ChatwinChris Chatwin, Phil BirchPhil BirchThe window unit in the design of the complex logarithmic r-¿ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-¿ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-¿ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-¿ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation. © 2009 SPIE.
History
Publication status
- Published
ISSN
0277-786XExternal DOI
Volume
7340Presentation Type
- paper
Event name
Optical Pattern Recognition XX; 16 April 2009 through 17 April 2009Event location
Orlando, FL, USAEvent type
conferenceISBN
978-081947606-7Department affiliated with
- Engineering and Design Publications
Notes
Proceedings of SPIE - The International Society for Optical EngineeringFull text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-02-06Usage metrics
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