Dedicated optoelectronic stochastic parallel processor for real-time image processing: motion-detection demonstration and design of a hybrid complementary-metal-oxide semiconductor– self-electro-optic-device-based prototype

Cassinelli, Álvaro; Chavel, Pierre; Desmulliez, Marc Phillipe Yves

doi:10.1364/ao.40.006479

Cited by 4 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Literature [10] compares the movement characteristics of wrestling feints in the process of backward bending and hip throwing. Literature [11] uses a dedicated optoelectronic random parallel processor for real-time image processing. Low-cost motion tracking experimental device is based on image processing and camera calibration technology [12].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Athletes’ Training Characteristics Based on Action Statistics of Image Processing

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Sports and physical exercise are so closely related that they cannot be described separately. The standardization of physical movements requires athletes to constantly improve their planning. Only when they approach the standard, the improvement of sports level is just around the corner. However, the traditional training standard method is limited by human factors and backward technology, and there are many drawbacks, and athletes’ training cannot reach the best state. In this paper, image deblurring is processed to get the reconstruction model of high-resolution image. Through the experiment on the statistics of the competition, the movement of transfer, out of bounds and arm holding in the standing stage, and the movement of rolling bridge and lifting and holding in the kneeling stage are predicted and prevented. For 55 kg, the key to win is the rolling bridge and lifting action; 60 kg attaches importance to the importance of tactical defense. These two lightweight competitions focus on comprehensive training, while the 120 kg heavyweight competition is more in pursuit of strength. Finally, the experiment runs well, and the data and effect can meet the design goal of this paper. The specific details of the optimization and improvement need to be improved in the next step.

show abstract

Section: Introductionmentioning

confidence: 99%

Analysis of Athletes’ Training Characteristics Based on Action Statistics of Image Processing

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…Nevertheless, with the functionalities presented above one can think of a processor which combines morphological filters, other local operations and thresholding as a set of basic procedures for parallel nonlinear optical image processing. To achieve high-speed operation of the proposed morphological processor it is necessary to replace optical thyristor arrays used in these proof-of-principle experiments by CMOS/MQW smart pixel arrays with intrachip electrical or optical and interchip optical interconnections [23][24][25]. Recently, apart from development of optoelectronic systems, a growing interest in dedicated electronic hardware implementations of parallel programmable ranked order filtering with a compact analog hardware in GaAs technology is observed [26][27][28][29].…”

Section: Future Work On Local Image Processorsmentioning

confidence: 99%

Optical implementations of threshold decomposition and morphological operations with dual-rail processing

2004

View full text Add to dashboard Cite

Fast parallel processing of gray-scale images and exact hard-clip thresholding are two important functionalities necessary in optoelectronic implementations of structural processors. The parallel nature of processing stems from optical implementation of local operations with arrays of active smart pixels. We have demonstrated a morphological image processor composed of arrays of bistable optoelectronic transceivers which are connected in differential pairs and work as comparators. The use of differential pairs of optical thyristors fabricated in GaAs technology allows to realize a dual rail architecture for this photonic morphological image processor. The processor consists of a thresholding module and a binary morphological processing module. The thresholding module decomposes gray level images into series of binary slices. In the binary morphological processing module operations are performed within a neighborhood defined by a structuring element implemented as a diffractive fan-out element. In the prototype set-up we demonstrate median filtering, dilation and erosion operations performed for an image of 8x8 pixels and threshold decomposition of 6 gray level images. In principle all rank order as well as morphological filters can be optically calculated in the set-up. Additional functionality of the processor is achieved with use of the electronic layer with digital cellular processors. The electronic layer, designed as an array of simple digital processors, realizes a set of operations on binary images using 4 bit programmable weights. Simulation results for 0.8 µm CMOS technology are presented. We discuss the limitations of the photonic morphological image processing with respect to bandwidth, parallelism and architecture of the processor.

show abstract

Towards local motion detection by the use of analog self electro-optic effect device

Tasso

Souza

2010

Opt. Express

View full text Add to dashboard Cite

We demonstrated the use of the analog self electro-optic effect device (SEED) as part of an artificial retina chip for the detection and estimation of local motion. The characterization was performed by comparing our chip to biological and computational models and to other artificial retina chips. Its main unique feature is the optical output, since most chips have electrical output. By combining the response of the chip with temporal information about the input image, it is possible to estimate the velocity perpendicular to an edge, including its direction.

show abstract

Dedicated optoelectronic stochastic parallel processor for real-time image processing: motion-detection demonstration and design of a hybrid complementary-metal-oxide semiconductor– self-electro-optic-device-based prototype

Cited by 4 publications

References 31 publications

Analysis of Athletes’ Training Characteristics Based on Action Statistics of Image Processing

Analysis of Athletes’ Training Characteristics Based on Action Statistics of Image Processing

Optical implementations of threshold decomposition and morphological operations with dual-rail processing

Towards local motion detection by the use of analog self electro-optic effect device

Contact Info

Product

Resources

About