Research on Distortion Invariant Recognition of a Planar Integrated Optical Correlator

Xu, Peng; Yang, Tao; Huang, Haixuan; Li, Xiongchao; Xiao, Yufei; Pan, Yao; Yang, Wei

doi:10.1109/jphot.2018.2805694

Cited by 6 publications

(7 citation statements)

References 20 publications

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“…3 is the optimized phase distribution of the filter, and its gray value 0-255 corresponds to the phase value of the filter 0-2π. The 8 layer neural network model not only reveal the physical process of the 4f optical correlator, but also is beneficial to transform the neural network for simulating the correlator with other structure in the future, such as 2f optical correlator, or oblique incident optical correlator [17], and it lays the foundation for the filter optimization of other structure correlator.…”

Section: Establishment Of Neural Network Correlation Recognition Modelmentioning

confidence: 99%

“…Our group has successfully applied the neural network algorithm to solve the problem of the microstructure distribution on the lower surface of the light guide plate [16], and posses many years of research experience in optical correlation recognition and micro optical design [17]- [23]. Based on the previous research, a novel method of neural network applied in optical correlation recognition is presented to enhance the poor performance in 4F optical correlator.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method to Realize Optical Correlation Recognition Based on Neural Network

Yang

Liang

et al. 2018

IEEE Photonics J.

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A neural network model is constructed according to 4F optical correlator. New optical filter is obtained by training the neural network. For recognition of distortion targets, the correlation peaks from correlator applying new filter are averagely increased up to 306.7% than applying the OTSDF filter, and correlation peaks are higher, sharper and easier to be distinguished, which indicates optical correlator with new filter have better performance in distortion invariant recognition.

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Section: Establishment Of Neural Network Correlation Recognition Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Method to Realize Optical Correlation Recognition Based on Neural Network

Yang

Liang

et al. 2018

IEEE Photonics J.

Self Cite

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“…Based on the research on sub-wavelength optical design and application accumulated by our research group [10][11][12][13][14][15][16][17][18][19], this paper proposes a method based on a simple periodic binary sub-wavelength structure [12,13] to design a terahertz broadband filter. A silicon-based terahertz wideband filter with a center frequency of 4.07 THz was designed.…”

Section: Introductionmentioning

confidence: 99%

Terahertz Wideband Filter Based on Sub-Wavelength Binary Simple Periodic Structure

et al. 2019

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In this paper, a silicon-based terahertz wideband filter was designed using rigorous couple wave theory to achieve high diffraction efficiency and wideband filtering performance. The optimal parameters, such as filter period, duty ratio, and groove depth, are given. The design value and tolerance analysis were carried out to obtain the allowable deviation range of each structural parameter of the filter. The device was fabricated and tested for performance. The experimental results were consistent with the design results, proving the feasibility of the design method and can be applied in terahertz, communication, imaging, and other fields.

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“…Other advantages of the VLC are the exceptionally fast time required by the entire process, the high SNR (signal-to-noise ratio) and the large values of the space-bandwidth product, together with characteristics of the matched filter such as robustness, efficiency, location accuracy and high capability of discrimination. On the other hand, this type of correlator also presents some drawbacks: the alignment of the components in the setup must be extremely precise; it is more complex than the JTC; the matched correlation filter is very sensitive both to rotations of the input image and to changes of the scale size [ 20 , 22 , 47 , 48 ].…”

Section: Classification and Overview Of The Principles Of Optical Cor...mentioning

confidence: 99%

Optical Correlators for Cryptosystems and Image Recognition: A Review

Drăgulinescu

2023

Sensors

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Optical correlators are efficient optical systems that have gained a wide range of applications both in image recognition and encryption, due to their special properties that benefit from the optoelectronic setup instead of an all-electronic one. This paper presents, to the best of our knowledge, the most extensive review of optical correlators to date. The main types are overviewed, together with their most frequent applications in the newest contributions, ranging from security uses in cryptosystems, to medical and space applications, femtosecond pulse detection and various other image recognition proposals. The paper also includes a comparison between various optical correlators developed recently, highlighting their advantages and weaknesses, to gain a better perspective towards finding the best solutions in any specific domain where these devices might prove highly efficient and useful.

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Research on Distortion Invariant Recognition of a Planar Integrated Optical Correlator

Cited by 6 publications

References 20 publications

A Novel Method to Realize Optical Correlation Recognition Based on Neural Network

A Novel Method to Realize Optical Correlation Recognition Based on Neural Network

Terahertz Wideband Filter Based on Sub-Wavelength Binary Simple Periodic Structure

Optical Correlators for Cryptosystems and Image Recognition: A Review

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