scholarly journals Improved Parallelization of Cell Contour Extraction Algorithm

2017 ◽  
Vol 20 (5) ◽  
pp. 740-747
Author(s):  
Suk Hyun Yu ◽  
Woo Hyun Cho ◽  
Hee Yong Kwon
Keyword(s):  
Contour Extraction ◽  
Extraction Algorithm ◽  
Cell Contour

Moving Object Detection and Tracking Based on the Contour Extraction and Centroid Representation

2019 ◽  
pp. 147-157
Author(s):  
Naveenkumar M ◽  
Sriharsha K. V. ◽  
Vadivel A
Keyword(s):  
Object Detection ◽  
Motion Tracking ◽  
Moving Object Detection ◽  
Moving Object ◽  
Absolute Difference ◽  
Contour Extraction ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Novel Approach ◽  
Extraction Algorithm

This chapter presents a novel approach for moving object detection and tracking based on contour extraction and centroid representation (CECR). Firstly, two consecutive frames are read from the video, and they are converted into grayscale. Next, the absolute difference is calculated between them and the result frame is converted into binary by applying gray threshold technique. The binary frame is segmented using contour extraction algorithm. The centroid representation is used for motion tracking. In the second stage of experiment, initially object is detected by using CECR and motion of each track is estimated by Kalman filter. Experimental results show that the proposed method can robustly detect and track the moving object.

Research and Implementation of Moving Object Contour Extraction Algorithm Based on GPU

2014 ◽  
Vol 643 ◽  
pp. 253-257
Author(s):  
Kai Min Zhao ◽  
Yu Ting Chen ◽  
Jun Li ◽  
Hao Yang ◽  
Li Ying Chen
Keyword(s):  
Parallel Processing ◽  
Mathematical Morphology ◽  
Implementation Process ◽  
Differential Method ◽  
Massive Data ◽  
Contour Extraction ◽  
Moving Targets ◽  
Video File ◽  
Extraction Algorithm ◽  
Morphology Algorithm

In this paper, frame differential method will be used to detect moving targets in a static background video file, and pre-contour can be obtained by binarizing the detected targets . However,, the result are not what was expected, so the expansion and corrosion of mathematical morphology are used to extract the final contour of moving targets. in the progress of dealing with massive data , mathematical morphology is not good enough to achieve the need of the real-time in video surveillance. Considering the dilation and erosion is a kind of parallel processing operations, in order to improve the speed of mathematical morphology operations, this paper offers detailed implementation process of the dilation algorithm for parallel computing on GPU. Experimental results showed that GPU parallel processing on mathematical morphology algorithm faster than the CPU serial processing.

Contour extraction algorithm for edge placement error measurement using machine learning

2020 ◽  
Author(s):  
Yosuke Okamoto ◽  
Shinichi Nakazawa ◽  
Akinori Kawamura ◽  
Tsugihiko Haga ◽  
Taihei Mori ◽  
...  
Keyword(s):  
Machine Learning ◽  
Error Measurement ◽  
Contour Extraction ◽  
Extraction Algorithm

Cell contour extraction on multi-threshold images

1992 ◽  
Vol 188 (4-5) ◽  
pp. 449-453 ◽  
Author(s):  
J. Barba ◽  
Li Yuan ◽  
J. Gil
Keyword(s):  
Contour Extraction ◽  
Cell Contour

Vascular Contour Extraction of MRS Regional Morphology Algorithm Based on Sobel Operator

2012 ◽  
Vol 424-425 ◽  
pp. 676-679
Author(s):  
Fang Xiao Cheng ◽  
Xiao Mei Lin ◽  
Na Na Dong
Keyword(s):  
Regional Growth ◽  
Decisive Role ◽  
Detection Algorithm ◽  
Contour Extraction ◽  
Positioning Accuracy ◽  
Sobel Operator ◽  
Contrast Enhanced ◽  
Extraction Algorithm ◽  
Morphology Algorithm

Through the study of the traditional vascular contour extraction algorithm, in this paper the means that vascular contour extraction of MRS regional morphology algorithm based on Sobel Operator is proposed. This method comprehensively applying regional growth algorithm and morphologic detection algorithm, and combining with Sobel operator through the correction and contrast enhanced, the result of vascular contour is more accurate and more continuous on this basis, which plays a decisive role. Experiments show that this method not only can effectively extract vascular outline and vascular contour positioning accuracy is higher, but also can effectively reduce the interference of noise to the image , Thereby this method improve the anti-interference ability of contour extraction for image

An efficient semi-automatic algorithm for cell contour extraction

1995 ◽  
Vol 179 (3) ◽  
pp. 270-276 ◽  
Author(s):  
H.-S. WU ◽  
J. BARBA
Keyword(s):  
Contour Extraction ◽  
Cell Contour ◽  
Automatic Algorithm

scholarly journals Object Contour Extraction Algorithm Combined Snake with Level Set

2014 ◽  
Vol 3 (5) ◽  
pp. 195-200
Author(s):  
JaeYong Hwang ◽  
Yingjun Wu ◽  
JongWhan Jang
Keyword(s):  
Level Set ◽  
Contour Extraction ◽  
Object Contour ◽  
Extraction Algorithm
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