Change detection and background extraction by linear algebra

Durucan, Emrullah; Ebrahimi, Touradj

doi:10.1109/5.959336

Cited by 114 publications

(59 citation statements)

References 16 publications

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“…One of the conventional techniques used in foreground detection is background subtraction [1][2][3][4][5][6][7][8][9][10][11][12]. Stauffer and Grimson [13] modeled each pixel as a mixture of Gaussians and used an on-line approximation to update the model.…”

Section: Related Workmentioning

confidence: 99%

Detection of Foreground Object for Video Surveillance Applications

Begum¹

2017

IJRASET

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This paper describes the simplest and efficient method to find the foreground objects in less computation time. Initially the video is converted into frames. Those frames are compressed by eliminating the redundant frames by extracting more informative frames. The correlation coefficient is used to find similar frames which are to be eliminated. The first frame is set as the background of the image. The background image is subtracted from all subsequent compressed frames so that we obtain foreground of the image. The morphological operation is performed on the foreground objects to obtain boundary of objects. The noise is removed by applying the median filter. Moore neighborhood algorithm is applied to the image to obtain objects. Those objects can be used for further processing in various applications.

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Section: Related Workmentioning

confidence: 99%

Detection of Foreground Object for Video Surveillance Applications

Begum¹

2017

IJRASET

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“…For the sake of comparison to other change detection methods on the same test images please refer to [5], [2].…”

Section: Discussionmentioning

confidence: 99%

“…are linearly independent, (2) detG > 0, (3) detG = 0, are equivalent. For a proof of this theorem refer to Huppert [9].…”

Section: Linear Dependence and The Gramian Matrixmentioning

confidence: 99%

“…In fact, we are not aware of comparable state-of-the-art methods which enable the detection of changes between several frames and color images. This paper presents in fact a possible extension of the previously presented concept of linear independence [5], [2] which was based on the detection of changes in gray-valued images. These papers also present comparisons to other state-of-theart change detection methods, detecting changes between two gray-valued images [10], [8], [14], [16], [1], [6], [11] .…”

Section: Introductionmentioning

confidence: 99%

“…However these images including an exhaustive description of their contents could be found in [2]. Finally, the definition of adaptive thresholds can be found in [4], [3].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Moving object detection between multiple and color images

Durucan

Ebrahimi

Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.

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Abstract-There are several publications dedicated to the description and analysis of change detection between two gray-value images. This paper now introduces new methods to detect moving objects between multiple images and to detect changes between color images or any type of multispectral images. We are not aware of methods giving the possibility to detect color changes and changes between multiple frames.All proposed change detectors in this chapter are based on the Gramian determinant, which provides low computational cost and is easy to implement. These features are very important due to the additional complexity of change detection between multiple as well as color images.

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Change Detection of Multi‐temporal Remote Sensing Images Based on Contourlet Transform and Ica

Zhaoqing

Tao

2016

Chinese J of Geophysics

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In order to improve the accuracy and computational efficiency of change detection of multi‐temporal remote sensing images, a change detection algorithm based on contourlet transform and independent component analysis (ICA) is proposed. Firstly, multi‐scale decomposition of image data is performed by using contourlet transform with multi‐scale, directionality and anisotropy. Then independent component analysis is carried out for the decomposed data. And the independent data components are separated by the improved fixed point ICA algorithm based on Newton iteration. Next the separated data components are transformed into image components. Finally, change detection is achieved by threshold segmentation and filtering for change image components. The experimental results show that, compared with the existing three change detection algorithms such as the algorithm based on PCA, the algorithm based on ICA and the algorithm based on wavelet transform and ICA, the proposed algorithm in this paper more effectively separates change information and reduces computational complexity. The obtained change image has higher accuracy and strong robustness with respect to the background.

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Change detection and background extraction by linear algebra

Abstract: Change detection plays a very important role in real-

Cited by 114 publications

References 16 publications

Detection of Foreground Object for Video Surveillance Applications

Detection of Foreground Object for Video Surveillance Applications

Moving object detection between multiple and color images

Change Detection of Multi‐temporal Remote Sensing Images Based on Contourlet Transform and Ica

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