A Moving Target Detection Algorithm Based on the Dynamic Background

Yu, Yangquan; Zhou, Chunguang; Huang, Lan; Yu, Zhezhou

doi:10.1109/cise.2009.5366582

Cited by 9 publications

(2 citation statements)

References 9 publications

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“…It is also affected by noise and changes in illumination due to weather conditions. Hence it can detect all positions of the foreground [4] [5].…”

Section: G(xy)=mentioning

confidence: 99%

Automated Detection, Locking and Hitting a Fast Moving Aerial Object by Image Processing (Suitable For Guided Missile)

Garg¹,

Rouf²,

Hafiz³

et al. 2016

IOSR

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Due to passive tracking, fire and forget capabilities and ease of operation of guided missiles have emerged as an important anti-aircraft arsenal. Detection of target in real time is a difficult task when object is dynamic and even harder when the object tends to move at speed counted in Mach numbers. Moving target detection is a key area in image processing, infusion of this technology to the purpose of tracking target and destroying as in guided missiles can be very effective as it will reduce network links, and GPS navigation in aggressive electronic warfare environments. Detecting moving objects in real-time is a challenging problem due to the computational limits and the motions of the camera. In this paper, we suggest a method for dynamic object detection and tracking on non-stationary cameras running within few milliseconds (ms) on a PC, and real-time on mobile devices. Detecting of object by background subtraction method does not give better results when object is moving very fast, object is very tiny and presence of lighting effect. In order to overcome these troubles, we propose a new method for Moving object Detection in Dynamic Background along with the development of a guided missile using the process. It achieves dynamic landscape using certain possibility of time and subsequent frame difference method and addresses the difficult scenario, where object is moving very fast and background changes frequently. The experimental results show that the proposed method can detect moving object more efficiently and completely in both cases online as well as offline video. The results indicate that the proposed algorithm outperforms the majority of earlier state-of-the-art algorithms not only in terms of accuracy, but also in terms of processing speed.

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“…It is also affected by noise and changes in illumination due to weather conditions. Hence it can detect all positions of the foreground [4] [5].…”

Section: G(xy)=mentioning

confidence: 99%

Automated Detection, Locking and Hitting a Fast Moving Aerial Object by Image Processing (Suitable For Guided Missile)

Garg¹,

Rouf²,

Hafiz³

et al. 2016

IOSR

View full text Add to dashboard Cite

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“…Low angle off axis camera is used by Adhere et al [14] to employ feature based tracking. For dynamic environments the background subtraction needs to be more robust by considering the ever changing metrics of the surroundings and this requires stochastic based methods implemented by [15], [16].The paper is organized as follows: Section 2 focusses on the motion detection paradigm and the related literature survey, Section 3 highlights the proposed algorithm and its modelling. Section 4 discusses the experimental results while practical implementation of the system on embedded platform is presented in section 5.…”

Section: Introductionmentioning

confidence: 99%

Robust and adaptive traffic surveillance system for urban intersections on embedded platform

Bharade

Gaopande

2014

2014 Annual IEEE India Conference (INDICON)

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The paper presents a real time traffic monitoring system that makes use of image processing algorithm to detect and estimate the of count of vehicles using motion detection approach. Traffic congestion is a serious issue, which is the root cause of a series of serious problems. Conventional traffic light controllers have limitations because they make use of the predefined hardware, whose functioning is governed according to program that does not have the flexibility of modification on real time basis. The proposed system makes use of a differential algorithm in order to determine the signaling duration of each lane of intersection. The system provides different delays for different junctions thus optimizing the waiting time of each user. This flexibility of timing and controlling prevents the congestion of vehicles in squares due to high waiting time for the green light. The traffic flux density determines the effective number of vehicles at any intersection and hence is critical in allocation of signaling duration to any intersection. Real time analysis presents many challenges in video analysis and in order to lower down the computational complexities, the algorithm makes use of simple background subtraction technique. The system has been tested for a number of video sequences. The results produced are extremely encouraging and hence the system can be applied in real time traffic control in urban areas.

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A moving objects detection in underwater video using subtraction of the background model

Prabowo

Hudayani

Purwiyanti

et al. 2017

2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)

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A Moving Target Detection Algorithm Based on the Dynamic Background

Cited by 9 publications

References 9 publications

Automated Detection, Locking and Hitting a Fast Moving Aerial Object by Image Processing (Suitable For Guided Missile)

Automated Detection, Locking and Hitting a Fast Moving Aerial Object by Image Processing (Suitable For Guided Missile)

Robust and adaptive traffic surveillance system for urban intersections on embedded platform

A moving objects detection in underwater video using subtraction of the background model

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