Particle Size and Position Measurement of Defocused Particle Based on Convolutional Neural Network

Xiangyun Zhang; Wu Zhou; Youxin Jiang; Xiangxuejie Xia

doi:10.3788/AOS202242.1912006

[1] Tropea C. Optical particle characterization in flows[J]. Annual Review of Fluid Mechanics, 43, 399-426(2011).

[2] Pentland A P. A new sense for depth of field[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 9, 523-531(1987).

[3] Mannan F, Langer M S. Blur calibration for depth from defocus[C], 281-288(2016).

[4] Han L Y, Wang L M, Liu B. A ranging algorithm based on edge diffusion function to describe the degree of scattered focus[J]. Sensor World, 17, 9-11(2011).

[5] Zhao P J, Wang H L, Wang B et al. Identification and tracking about three-dimensional microscopic defocusing particle[J]. Computer Measurement & Control, 24, 298-300, 303(2016).

[6] Song X L, Li S, Gu M T et al. Three-dimensional reconstruction of micro-scale flow field based on light field microscopic imaging[J]. Acta Optica Sinica, 39, 1011002(2019).

[7] Wang X X, Zhou W, Wang F T et al. Particle streak velocimetry based on defocused imaging[J]. Acta Optica Sinica, 41, 1912004(2021).

[8] Zhou W, Jin N, Jia M H et al. Three-dimensional positioning method for moving particles based on defocused imaging using single-lens dual-camera system[J]. Chinese Optics Letters, 14, 31201-31205(2016).

[9] Luo X. Particle restoration and size measurement based on defocused images[D](2019).

[10] Zhou W, Luo X, Chen B T et al. Estimation of particle depth from two defocused images using the Fourier transform[J]. Particuology, 49, 48-54(2020).

[11] Huang J P, Shi Y H, Gao Y. Multi-scale Faster-RCNN algorithm for small object detection[J]. Journal of Computer Research and Development, 56, 319-327(2019).

[12] Newby J M, Schaefer A M, Lee P T et al. Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D[J]. Proceedings of the National Academy of Sciences of the United States of America, 115, 9026-9031(2018).

[13] Tang J, Wang K Q, Zhang W et al. Deep learning based image restoration method of optical synthetic aperture imaging system[J]. Acta Optica Sinica, 40, 2111001(2020).

[14] Li W J, Gai S Y, Yu J et al. Absolute phase recovery of single frame composite image based on convolutional neural network[J]. Acta Optica Sinica, 2312001(2021).

[15] Cheng W T, Ren D W, Wang Q L. Defocus deblurring algorithm based on deep recurrent neural network[J/OL]. Application Research of Computers, 1-7.

[16] Chen Q J, Li Y, Chai Y Z. A multi-focus image fusion algorithm based on depth learning[J]. Laser & Optoelectronics Progress, 55, 071015(2018).

[17] Zhou W, Tropea C, Chen B T et al. Spray drop measurements using depth from defocus[J]. Measurement Science and Technology, 31, 075901(2020).

[18] Goodfellow I, Bengio Y, Courville A[M]. Deep learning, 326-366(2016).

[19] Xia Y, Xiao J Q, Weng Y S. Surface defect detection of polarizer based on improved Faster-RCNN[J]. Optical Technique, 47, 695-702(2021).

[20] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. https://arxiv.org/abs/1409.1556

[21] Evangelidis G D, Psarakis E Z. Parametric image alignment using enhanced correlation coefficient maximization[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30, 1858-1865(2008).