Detecting for high speed flying object using image processing on target place

Cho, Changhee; Kim, Jisue; Kim, Jinsul; Lee, Sang-Joon; Kim, Kuinam J.

doi:10.1007/s10586-015-0525-x

Cited by 5 publications

(6 citation statements)

References 16 publications

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“…Once the winner-neuron is determined, the weight vector of winnerneuron will be updated according to Equation (5).…”

Section: The Overall Architecturementioning

confidence: 99%

“…High-speed image capture is one of the fundamental tasks for numerous industrial and scientific applications such as target tracking, optical scientific measurement, autonomous vehicles [1][2][3][4][5], etc. Generally, in high-speed vision systems, the challenges of insufficient bandwidth and storage are increasingly severe and gradually become the bottlenecks.…”

Section: Introductionmentioning

confidence: 99%

“…W s (t) and W s (t + 1) represent the weight vectors of the winner-neuron before and after the updating process, respectively. As shown in Equation (5), the update procedure can be regarded as a gradual reduction of the component-wise difference between the input vector and weight vector of the winner-neuron. Geometrically speaking, the weight vector of the winner-neuron is moved towards the input vector and the step size of weight vector movement is affected by α(t).…”

Section: Introductionmentioning

confidence: 99%

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A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression

et al. 2017

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This paper presents a compact vector quantizer based on the self-organizing map (SOM), which can fulfill the data compression task for high-speed image sequence. In this vector quantizer, we solve the most severe computational demands in the codebook learning mode and the image encoding mode by a reconfigurable complete-binary-adder-tree (RCBAT), where the arithmetic units are thoroughly reused. In this way, the hardware efficiency of our proposed vector quantizer is greatly improved. In addition, by distributing the codebook into the multi-parallel processing sub-blocks, our design obtains a high compression speed successfully. Furthermore, a mechanism of partial vector-component storage (PVCS) is adopted to make the compression ratio adjustable. Finally, the proposed vector quantizer has been implemented on the field programmable gate array (FPGA). The experimental results indicate that it respectively achieves a compression speed of 500 frames/s and a million connections per second (MCPS) of 28,494 (compression ratio is 64) when working at 79.8 MHz. Besides, compared with the previous scheme, our proposed quantizer achieves a reduction of 8% in hardware usage and an increase of 33% in compression speed. This means the proposed quantizer is hardware-efficient and can be used for high-speed image compression.

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“…Once the winner-neuron is determined, the weight vector of winnerneuron will be updated according to Equation (5).…”

Section: The Overall Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression

et al. 2017

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“…Both options provide effective solutions for precisely capturing object position and time data together (Ishii et al, 2017;Jezeršek, 2009). Today, it is necessary for measuring high-speed objects using a cost-effective solution (Cho et al, 2016;Sozen et al, 2019). In real experiments, various parameters are effecting the precision and accuracy of a flight measuring setup such as object launcher, size, and shape of objects, the response time of the sensor, frame per second (FPS) for fast cameras .…”

Section: Introductionmentioning

confidence: 99%

“…There are limited studies on low-cost object flight speed measuring solutions for indoor applications. An indoor application (Cho et al, 2016) is offering a solution using image processing techniques such as Canny Edge, Contour, Calibration, Transform process, and Threshold for detecting the high-speed flying objects. In one study (Shrivastava et al, 2006), binary proximity sensors are used for target tracking effectively.…”

Section: Introductionmentioning

confidence: 99%

Development of an Open-Source Object Flight Speed Measuring Setup for Indoor Measurements

Turan

Karasu

Yetişkin

et al. 2021

Soma Meslek Yüksekokulu Teknik Bilimler Dergisi

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Time of flight measurement is an important procedure for indoor object flight speed measurement applications. Measuring a fast-moving object is very difficult such as military and sport shooting. Today, there is a requirement for measuring high-speed objects using a cost-effective solution. The speed detection processing requires two referencing points from flight start to end. The difference between these two points and time parameters leads to calculating speed. In-flight speed detection applications mostly an object is thrown by a launcher and measurements are conducted in a linear horizontal measurement line. The terminals of this line are referred to these two points. There are light-based solutions such as infra-red (IR) sensors, fast cameras for indoor speed measurement. However, commercial solutions based on sensors or fast cameras are expensive options and these solutions are not easily affordable for research facilities and laboratories with low-budget. In this study, an object flight speed detection setup is demonstrated for indoor measurements. The accuracy of the demonstrated setup was found 94%. The results show that is possible to use a microcontroller (MCU) with two IR sensor for calculating the flight speed with low-cost and high accuracy.

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Intelligent Agents for Observation and Containment of Malicious Targets Organizations

Silva¹,

Araújo²,

Ferro³

et al. 2021

Lecture Notes in Computer Science

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Detecting for high speed flying object using image processing on target place

Cited by 5 publications

References 16 publications

A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression

A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression

Development of an Open-Source Object Flight Speed Measuring Setup for Indoor Measurements

Intelligent Agents for Observation and Containment of Malicious Targets Organizations

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