Deep Convolutional Sequence Approach Towards Real-Time Intelligent Optical Scanning

Author(s):  
Mansi Mahendru ◽  
Sanjay Kumar Dubey ◽  
Divya Gaur

Visual text recognition is the most dynamic computer vision application due to its rising demand in several applications like crime scene detection, assisting blind people, digitizing, book scanning, etc. However, numerous research works were executed on static visuals having organized text and on captured video frames in the past. The key objective of this study is to develop the real-time intelligent optical scanner that will extract every sequence of text from high-speed video, noisy visual input, and offline handwritten script. The scientific work has been carried out with the combination of multiple deep learning approaches, namely EAST, CNN, and Bi-LSTM with CTC. The system is trained and tested on four public datasets (i.e., ICDAR 2015, SVT, Synth-Text, IAM-3.0) and measured on the basis of recall, precision, and f-measure. Based on the challenges, performance has been examined under three different categories, and the outcomes are optimistic and encouraging for future advancement.

2013 ◽  
Vol 365-366 ◽  
pp. 654-657
Author(s):  
Xue Dong Xie ◽  
Wei Ling Zhao

ATOS three-dimensional optical scanner is one of the most advanced technologically three-dimensional optical scanning devices. It can automatically put together the multiple scan view image by the reference point of the measurement system, with high accuracy, high speed Etc. It is widely used in automobiles. The paper combines with the experience in vehicle measurements, analysis the error cause in the actual use, points out ways to reduce or eliminate error. It has the great application value to actual measurement.


2020 ◽  
Vol 34 (07) ◽  
pp. 10933-10940
Author(s):  
Xiaochen Han ◽  
Bo Wu ◽  
Zheng Shou ◽  
Xiao-Yang Liu ◽  
Yimeng Zhang ◽  
...  

Snapshot compressive imaging (SCI) cameras capture high-speed videos by compressing multiple video frames into a measurement frame. However, reconstructing video frames from the compressed measurement frame is challenging. The existing state-of-the-art reconstruction algorithms suffer from low reconstruction quality or heavy time consumption, making them not suitable for real-time applications. In this paper, exploiting the powerful learning ability of deep neural networks (DNN), we propose a novel Tensor Fast Iterative Shrinkage-Thresholding Algorithm Net (Tensor FISTA-Net) as a decoder for SCI video cameras. Tensor FISTA-Net not only learns the sparsest representation of the video frames through convolution layers, but also reduces the reconstruction time significantly through tensor calculations. Experimental results on synthetic datasets show that the proposed Tensor FISTA-Net achieves average PSNR improvement of 1.63∼3.89dB over the state-of-the-art algorithms. Moreover, Tensor FISTA-Net takes less than 2 seconds running time and 12MB memory footprint, making it practical for real-time IoT applications.


1995 ◽  
Author(s):  
Rod Clark ◽  
John Karpinsky ◽  
Gregg Borek ◽  
Eric Johnson
Keyword(s):  

Author(s):  
Kenneth Krieg ◽  
Richard Qi ◽  
Douglas Thomson ◽  
Greg Bridges

Abstract A contact probing system for surface imaging and real-time signal measurement of deep sub-micron integrated circuits is discussed. The probe fits on a standard probe-station and utilizes a conductive atomic force microscope tip to rapidly measure the surface topography and acquire real-time highfrequency signals from features as small as 0.18 micron. The micromachined probe structure minimizes parasitic coupling and the probe achieves a bandwidth greater than 3 GHz, with a capacitive loading of less than 120 fF. High-resolution images of submicron structures and waveforms acquired from high-speed devices are presented.


2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Florian Roessler ◽  
André Streek

Abstract In laser processing, the possible throughput is directly scaling with the available average laser power. To avoid unwanted thermal damage due to high pulse energy or heat accumulation during MHz-repetition rates, energy distribution over the workpiece is required. Polygon mirror scanners enable high deflection speeds and thus, a proper energy distribution within a short processing time. The requirements of laser micro processing with up to 10 kW average laser powers and high scan speeds up to 1000 m/s result in a 30 mm aperture two-dimensional polygon mirror scanner with a patented low-distortion mirror configuration. In combination with a field programmable gate array-based real-time logic, position-true high-accuracy laser switching is enabled for 2D, 2.5D, or 3D laser processing capable to drill holes in multi-pass ablation or engraving. A special developed real-time shifter module within the high-speed logic allows, in combination with external axis, the material processing on the fly and hence, processing of workpieces much larger than the scan field.


Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4865
Author(s):  
Kinzo Kishida ◽  
Artur Guzik ◽  
Ken’ichi Nishiguchi ◽  
Che-Hsien Li ◽  
Daiji Azuma ◽  
...  

Distributed acoustic sensing (DAS) in optical fibers detect dynamic strains or sound waves by measuring the phase or amplitude changes of the scattered light. This contrasts with other distributed (and more conventional) methods, such as distributed temperature (DTS) or strain (DSS), which measure quasi-static physical quantities, such as intensity spectrum of the scattered light. DAS is attracting considerable attention as it complements the conventional distributed measurements. To implement DAS in commercial applications, it is necessary to ensure a sufficiently high signal-noise ratio (SNR) for scattered light detection, suppress its deterioration along the sensing fiber, achieve lower noise floor for weak signals and, moreover, perform high-speed processing within milliseconds (or sometimes even less). In this paper, we present a new, real-time DAS, realized by using the time gated digital-optical frequency domain reflectometry (TGD-OFDR) method, in which the chirp pulse is divided into overlapping bands and assembled after digital decoding. The developed prototype NBX-S4000 generates a chirp signal with a pulse duration of 2 μs and uses a frequency sweep of 100 MHz at a repeating frequency of up to 5 kHz. It allows one to detect sound waves at an 80 km fiber distance range with spatial resolution better than a theoretically calculated value of 2.8 m in real time. The developed prototype was tested in the field in various applications, from earthquake detection and submarine cable sensing to oil and gas industry applications. All obtained results confirmed effectiveness of the method and performance, surpassing, in conventional SM fiber, other commercially available interrogators.


Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5279
Author(s):  
Dong-Hoon Kwak ◽  
Guk-Jin Son ◽  
Mi-Kyung Park ◽  
Young-Duk Kim

The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.


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