Camera-based shooting simulator using color thresholding techniques

Soetedjo, Aryuanto; Ashari, Mochamad; Mahmudi, Ali; Nakhoda, Yusuf Ismail

doi:10.1109/ica.2013.6734073

Cited by 10 publications

(14 citation statements)

References 4 publications

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“…Thresholding [27,28,[32][33][34][35][36] Template matching [6,7,12,[24][25][26] Colour-based techniques [27][28][29][30][31] Camera or display filters [23,[37][38][39][40][41][42][43] Video and camera network [32,34,38,[44][45][46][47][48][49] Hardware-based approaches [30,50] Classical vision techniques in combination with fuzy rule-based systems [5,7,[9][10][11][12] presented in Table 1. Note that it is necessary to analyze the brightness of the image to correctly calculate the threshold value of the laser spot.…”

Section: Technique Used Workmentioning

confidence: 99%

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Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system

Clemente

Chávez

Vega

et al. 2015

Applied Soft Computing

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Section: Technique Used Workmentioning

confidence: 99%

“…A different technique that is also applied to detect the laser spot is employed in [27][28][29][30][31]. The algorithm uses different colour bands: red, green and blue (RGB) and Hue, Saturation and Intensity (HSI) to provide with a richer information that is useful for detecting the laser spot on an image.…”

Section: Technique Used Workmentioning

confidence: 99%

Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system

Clemente

Chávez

Vega

et al. 2015

Applied Soft Computing

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“…In another type of shooting simulator which is camera based, is having the camera attached on the weapon to catch the laser spot which is fired by pressing the trigger of the weapon. Red colour thresholding technique has been used to detect the laser spot and the score of shooting has been calculated with the same algorithm [2].…”

Section: )mentioning

confidence: 99%

Small arm intelligent training aid

Dake¹,

Autee²

2015

2015 International Conference on Pervasive Computing (ICPC)

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The Deployment of SAITA is in the direction of developing the unique firing skill into the soldier. The proposed system is portable, simple, and cost effective and resource saving equipment which can be utilized by troops even during small breaks in the deployment to practice their weapon training and remove the need to carry out firing practice at SA ranges. This equipment can be issued down to platoon level and can be utilized by platoon commanders to train their command in basic as well as advanced firing drills and also improve the accuracy and consistency of SA firer without resorting the actual firing as well as during actual firing. The proposed system is Matlab based system with RF communication. It provides the miss distance of aim point from target point as well as of bullet from an aim point passes through the target plane. Initial work indicates that a lowcost solution can achieve millimeter-level accuracy irrespective of velocity over a wide range of environmental conditions.

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“…The camera is connected to the computer for further processes. While in the second method, the camera is mounted on the weapon (Soetedjo et al, 2013;2014;Ladha et al, 2010;. The latter one has an advantage i.e., allowing the multi shooters shot on a single target.…”

Section: Introductionmentioning

confidence: 99%

“…To detect the laser spot, (Lapointe and Godin, 2005) employed the thresholding method in the intensity images. The RGB color thresholding methods were employed in (Liang and Kong, 2006;Soetedjo et al, 2013). While the HSV color thresholding techniques were employed in (Kim et al, 2007;Widodo et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Low Cost Shooting Simulator Based on a Single Board Computer

Soetedjo¹,

Mahmudi²,

Ashari³

et al. 2015

American Journal of Applied Sciences

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This paper proposes the camera on weapon system used as the shooting simulator. The single board computer (Raspberry Pi module) is used as the main processor. The OpenCV is implemented on the embedded system to perform the image processing task. The aim of the proposed camera on weapon system is to detect the position of the markers on the target and the laser spot. The detected coordinates are sent to the personal computer using a wireless communication provided by a low power Zigbee protocol. The performance of the proposed system using two camera systems (the Web-Camera and the Raspberry Pi-Camera) are evaluated. Both systems achieve the higher performances in the shooting detection which is greater than 85%, the target detection error which is lower than 0.8% and the small displacement on the arrangement of the camera and the laser pointer which is lower than one pixel. The Raspberry Pi-Camera system has a fast processing speed of 27 fps, while the processing speed of the Web-Camera system is 17 fps.

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Camera-based shooting simulator using color thresholding techniques

Cited by 10 publications

References 4 publications

Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system

Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system

Small arm intelligent training aid

Low Cost Shooting Simulator Based on a Single Board Computer

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