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Anti-noise moving object detecting method based on frequency domain processing

A moving target and detection method technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as failure, low image resolution, and inability to solve the problem of moving target detection well, so as to filter out pollution and have anti-corrosion noise effect

Active Publication Date: 2014-08-13
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

Excessive noise will lead to unsatisfactory or even complete failure of traditional motion detection methods
For example, the classic moving target detection method - the mixed Gaussian model, through the statistical model to estimate the current frame pixel value in order to distinguish the foreground and background, the effect is as follows figure 2 As shown in (b1-b4), the visual background descriptor (ViBe), as a mainstream moving object detection, is widely used by using the idea of ​​classification cascade, but it can not solve the problem of noise under the condition of Moving target detection problem, the effect is as follows figure 2 As shown in (d1-d4): The relevant research on target detection using frequency domain information mainly focuses on the detection of radar and infrared images with low image resolution, and there is no related specific algorithm for the detection of moving targets in low-light environments

Method used

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Embodiment Construction

[0031] Such as figure 1 As shown, the method of the present invention will be described with reference to the following examples:

[0032] First, the processing interval of image frames is 10 frames, that is, the value of the frame number K in the content of the invention is 10. The size of the collected noisy image sequence is 320×240, and the size of each image block is 3×3. The image blocks at the same position of the 10 frames of images are vectorized to form a matrix X with a size of 9×10.

[0033] Perform a two-dimensional Fourier transform on the matrix X to obtain its spectral energy map:

[0034] F ( w , v ) = X n = 0 N - 1 X k = 0 K - 1 exp ( - 2 πi NK * ( w * n + v * k ) )

[0035] In the formula, the sizes of N and K are 9 and 10, respectively, and the sizes of w and v are the same as N and K.

[0036] Filter the obtained spectral energy map F(w,v):

[0037] P ( w ...

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Abstract

The invention discloses an anti-noise moving object detecting method based on frequency domain processing and belongs to the field of digital image processing. The anti-noise moving object detecting method comprises the steps that firstly, two-dimension Fourier transform projection is conducted on a collected image, so that image frequency domain information is obtained; secondly, through a low-pass filter, the low-frequency portion of a frequency spectrogram is selected and processed; finally, according to the change tendency of the low-frequency frequency spectrum of a front image and a rear image of the image, a moving target is selected out through a frequency spectrum energy function. After frequency domain change and low-frequency selection, noise information at the high frequency is effectively filtered out, so that the moving object detecting method has the anti-noise performance, and the moving object existing in the noise background can be accurately extracted.

Description

Technical field [0001] The invention relates to the field of digital image processing, in particular to an anti-noise moving target detection method based on frequency domain processing under the condition that an image sequence is polluted by noise. Background technique [0002] In the past ten years, with the popularization of digital technology and the improvement of computing power, moving target detection based on computer vision technology has received close attention and research from domestic and foreign scholars. Moving target detection refers to a method of accurately and completely extracting moving targets from a given image sequence or surveillance video. The extracted moving target information is the basis of high-level video processing technologies such as tracking, target recognition, and behavior understanding. As a key technology in the intelligent video surveillance system, from the application point of view, moving object detection can be used in intelligent ...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 刘煜张茂军肖华欣徐玮熊志辉
Owner NAT UNIV OF DEFENSE TECH
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