The effects of image background on velocity computation of moving objects

Mahmoud, Sabri A.; Afifi, M.; Green, R. J.

doi:10.1016/0745-7138(90)90009-v

Cited by 7 publications

(4 citation statements)

References 3 publications

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“…The effects of image background on the velocity computation of moving objects using the above model is addressed in Ref. 25. The analysis shows that the technique is applicable to real world scenes with nonzero background (viz., constant, time-invariant, and time-varying background).…”

Section: Analytical Formulationmentioning

confidence: 99%

Use of fourier and hartley transforms in motion estimation: A comparative study

Mahmoud

1991

Int J Imaging Syst Tech

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A comparison between the use of Fourier and Hartley transforms for motion estimation of multiple moving objects in image sequences is presented. The spectrum of the two transforms show that the temporal frequencies at the peaks (of the spectrum) is related to the velocity of the moving objects. The analysis shows that the Hartley technique is faster and requires less memory space than the Fourier technique. However, it gives the velocity of the moving objects but not the direction. The Fourier spectrum, on the other hand, gives the velocity and direction. An efficient implementation is possible by using the Hartley transform to estimate the temporal frequencies of the peaks and hence the velocities. The fast Fourier transform is then used to compute the spectrum at those peaks. The direction is easily found from the Fourier spectrum by reversing the sign of the temporal frequency corresponding to the peak.

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Section: Analytical Formulationmentioning

confidence: 99%

Use of fourier and hartley transforms in motion estimation: A comparative study

Mahmoud

1991

Int J Imaging Syst Tech

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“…Mahmoud et. al [2] and Porat and Friedlander [3] proposed the method using 3-dimensional Fourier transform. Kendall and Jacobi [4] and Fleet and Jepson [5] proposed the method using velocity filter bank.…”

Section: Introductionmentioning

confidence: 99%

“…Most of them process image sequences on the assumption that the targets move with constant velocities [1][2][3][4][5]. Mahmoud et.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, there has been a growing interest in detection of small low-contrast objects from optical or infrared (IR) image sequences [1][2][3][4][5][6][7][8][9][10][11][12]. The problem of detecting small low-contrast objects arises, for example, when we detect small moving targets from an on-board JR sensor [6,12], and when we detect meteors, asteroids and satellites in the night sky from an array of charge coupled device (CCD) sensors on the focal plane of a telescope [1,8,11].…”

Section: Introductionmentioning

confidence: 99%

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<title>Small target detection from image sequences using recursive max filter</title>

1995

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This paper presents a new method for detection of small moving targets from noisy image sequences using a recursive filter, which contains a local maximum filter in the feedback loop. Since all the procedures contained in this method can be implemented by fully parallel algorithm, this method can be realized by a neural network and real-time processing is possible for image sequences at high frame rates. First we investigate the performance of the method on the assumption that the targets move randomly in an image plane and the background noise is white both in time and space. The results show that the proposed method has the ability to suppress the background noise and enhances small moving targets, and that the targets are detected only by thresholding after the processing of the recursive filter. There can be other backgrounds such as clutters and stationary objects. It is also shown that the above method is applicable after preprocessing of conventional time difference method, and is able to suppress these backgrounds. Next we analyze the performance of the method using the property of order statistics. The performance measure is the output signal-to-noise ratio (SNR) and is represented analytically as a function of input SNR and the parameters included in the method. Finally, the recursive filter is optimized using the result of the analysis.

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Motion estimation based on modified Fourier spectrum

Mahmoud

1991

Information Processing Letters

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The effects of image background on velocity computation of moving objects

Cited by 7 publications

References 3 publications

Use of fourier and hartley transforms in motion estimation: A comparative study

Use of fourier and hartley transforms in motion estimation: A comparative study

<title>Small target detection from image sequences using recursive max filter</title>

Motion estimation based on modified Fourier spectrum

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