A new method of moving object detection using adaptive filter

Hsia, Chih-Hsien; Wu, Tung-Lin; Chiang, Jen‐Shiun

doi:10.1007/s11554-014-0404-3

Cited by 11 publications

(2 citation statements)

References 16 publications

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“…Digital images obtained from the video frames are used for many applications. However, such encountered factors as the environment, transmission channels and imperfections in the video acquisition systemespecially due to cheap cameras-cause a decrease in image quality [2,3]. To date, many techniques have been developed to improve video quality.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Statistical Methods for Obtaining Image from Video Frames Based on Development of Quality Metric

Güngör

2021

Sakarya University Journal of Science

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Digital images obtained from the video frames have an important role in different areas. Many image processing techniques have been applied to digital images for different purposes such as edge detection. For a better image processing application, it is very important to obtain images with less oscillation from the video. However, the factors such as camera and environment cause differences among the consecutive frames. These differences cause images with oscillation. Statistical methods can be used to obtain images with less oscillation from multiple frames. In this paper, we developed a quality metric to compare the frames or images in accordance with the quantity of oscillation. A comparative study of statistical methods used to obtain the images with less oscillation from the video frames was presented. Images were obtained by using four statistical methods for the different numbers of frames. This study also focuses on evaluating how the statistical method choice affects the oscillation of images using the proposed quality metric and comparing the processing times of the methods.

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Section: Introductionmentioning

confidence: 99%

Comparison of Statistical Methods for Obtaining Image from Video Frames Based on Development of Quality Metric

Güngör

2021

Sakarya University Journal of Science

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“…Problems such as environment, transmission channels, and imperfections in the image acquisition system, especially cheap cameras, cause poor quality of the images taken from the camera [17][18]. Thus, the edges in edge images obtained as a result of edge detection algorithms may not continue on a single line as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Edge Detection Methods According to Fake Edge and Area Calculation Performances

Güngör

Polat

2020

International Journal of Automotive Science and Technology

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Determining the borders of the objects in the images and detection of the edges is an important step for image processing applications. In this study, the areas of different objects were calculated using edge detection methods. The edges of real-time images taken from the camera were detected with traditionally used Sobel, Prewitt and Canny filters. In addition, these filters were applied to the images obtained using Basic Global Thresholding (BGT) pre-processing and Mean Thresholding (MT) pre-processing to detect the edges in the image. After eliminating the fake edges in the edge images, the areas of the obtained images were calculated. The methods used in this paper were compared according to the fake edge and the area calculation performances.

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Operator Inequalities Involved Wiener–Hopf Problems in the Open Unit Disk

Ibrahim

2019

Springer Optimization and Its Applications

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A new method of moving object detection using adaptive filter

Cited by 11 publications

References 16 publications

Comparison of Statistical Methods for Obtaining Image from Video Frames Based on Development of Quality Metric

Comparison of Statistical Methods for Obtaining Image from Video Frames Based on Development of Quality Metric

Comparison of the Edge Detection Methods According to Fake Edge and Area Calculation Performances

Operator Inequalities Involved Wiener–Hopf Problems in the Open Unit Disk

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