A prior-knowledge-based threshold segmentation method of forward-looking sonar images for underwater linear object detection

2016 ◽  
Vol 55 (7S1) ◽  
pp. 07KG06 ◽  
Author(s):  
Lixin Liu ◽  
Hongyu Bian ◽  
Shin-ichi Yagi ◽  
Xiaodong Yang
Keyword(s):  
Object Detection ◽  
Prior Knowledge ◽  
Segmentation Method ◽  
Threshold Segmentation ◽  
Knowledge Based ◽  
Linear Object ◽  
Sonar Images ◽  
Forward Looking

A submarine pipeline segmentation method for noisy forward-looking sonar images using global information and coarse segmentation

2021 ◽  
Vol 112 ◽  
pp. 102691
Author(s):  
Weiyu Chen ◽  
Zhi Liu ◽  
Hongwei Zhang ◽  
Minyu Chen ◽  
Yupeng Zhang
Keyword(s):  
Global Information ◽  
Submarine Pipeline ◽  
Segmentation Method ◽  
Sonar Images ◽  
Forward Looking

Study of Segmentation Threshold Based on Wavelet Transform

2013 ◽  
Vol 756-759 ◽  
pp. 3855-3859
Author(s):  
Jian Yi Li ◽  
Hui Juan Wang
Keyword(s):  
Wavelet Transform ◽  
Digital Image ◽  
Region Growing ◽  
Detection Methods ◽  
Mathematical Tool ◽  
Matlab Simulation ◽  
Segmentation Method ◽  
Transform Method ◽  
Threshold Segmentation ◽  
Digital Image Enhancement

Based on the research of the four kinds of algorithms of digital image segmentation, based on edge detection methods, based on region growing method, threshold segmentation method and digital image threshold segmentation method based on wavelet transform, using MATLAB simulation of all digital image enhancement and segmentation process, the obtained results are analyzed, proving the threshold segmentation wavelet transform method has unparalleled advantages in information extraction in medical image. Wavelet transform is a mathematical tool widely used in recent years, compared with the Fu Liye transform, the window of Fu Liye transform, wavelet transform is the local transform of space and frequency, it can be very effective in extracting information from the signal [[1.

scholarly journals Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA

2017 ◽  
Vol 221 ◽  
pp. 427-436 ◽  
Author(s):  
Anthony L. Schroeder ◽  
Dalma Martinović-Weigelt ◽  
Gerald T. Ankley ◽  
Kathy E. Lee ◽  
Natalia Garcia-Reyero ◽  
...  
Keyword(s):  
Prior Knowledge ◽  
River Basin ◽  
Biological Effects ◽  
Knowledge Based

A noise reduction method for semi-supervised community detection based on harmonic function

2018 ◽  
Vol 32 (14) ◽  
pp. 1850166 ◽  
Author(s):  
Lilin Fan ◽  
Kaiyuan Song ◽  
Dong Liu
Keyword(s):  
Harmonic Function ◽  
Prior Knowledge ◽  
Community Detection ◽  
Detection Methods ◽  
Detection Process ◽  
Knowledge Based ◽  
Detection Approach ◽  
Series Of Experiments ◽  
Novel Strategy ◽  
The Impact

Semi-supervised community detection is an important research topic in the field of complex network, which incorporates prior knowledge and topology to guide the community detection process. However, most of the previous work ignores the impact of the noise from prior knowledge during the community detection process. This paper proposes a novel strategy to identify and remove the noise from prior knowledge based on harmonic function, so as to make use of prior knowledge more efficiently. Finally, this strategy is applied to three state-of-the-art semi-supervised community detection methods. A series of experiments on both real and artificial networks demonstrate that the accuracy of semi-supervised community detection approach can be further improved.

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