scholarly journals Spectrogram Enhancement By Edge Detection Approach Applied To Bioacoustics Calls Classification

2012 ◽  
Vol 3 (2) ◽  
pp. 1-20 ◽  
Author(s):  
W.B Hussein
Keyword(s):  
Edge Detection ◽  
Detection Approach

scholarly journals Correct and Crisp Edge Detection Approach based on Dense Network

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Xiaohua Li ◽  
Guangxiao Niu ◽  
Xiangxiang Li ◽  
Xiaoli Wang ◽  
Gang Shi
Keyword(s):  
Edge Detection ◽  
Dense Network ◽  
Detection Approach

scholarly journals An Multi-scale Edge Detection Approach

2012 ◽  
Vol 25 ◽  
pp. 1616-1620 ◽  
Author(s):  
Chen Zhigang ◽  
Cui Yueli ◽  
Chen Aihua
Keyword(s):  
Edge Detection ◽  
Multi Scale ◽  
Detection Approach

scholarly journals An improved edge detection approach and its application in defect detection

2017 ◽  
Vol 244 ◽  
pp. 012017 ◽  
Author(s):  
Vilas H Gaidhane ◽  
Navdeep ◽  
Asha Rani ◽  
Vijander Singh
Keyword(s):  
Edge Detection ◽  
Defect Detection ◽  
Detection Approach

Using Local Edge Pattern Descriptors for Edge Detection

2017 ◽  
Vol 32 (03) ◽  
pp. 1850006 ◽  
Author(s):  
Yu Wang ◽  
Na Zhang ◽  
Huaixin Yan ◽  
Min Zuo ◽  
Cuiling Liu
Keyword(s):  
Edge Detection ◽  
Vital Role ◽  
Detection Methods ◽  
Weighted Fusion ◽  
Edge Strength ◽  
Detection Approach ◽  
Segmentation Pattern ◽  
Edge Detection Method ◽  
Local Edge ◽  
Edge Pattern

Edge detection is an active and critical topic in the field of image processing, and plays a vital role for some important applications such as image segmentation, pattern classification, object tracking, etc. In this paper, an edge detection approach is proposed using local edge pattern descriptor which possesses multiscale and multiresolution property, and is named varied local edge pattern (VLEP) descriptor. This method contains the following steps: firstly, Gaussian filter is used to smooth the original image. Secondly, the edge strength values, which are used to calculate the edge gradient values and can be obtained by one or more groups of VLEPs. Then, weighted fusion idea is considered when multiple groups of VLEP descriptors are used. Finally, the appropriate threshold is set to perform binarization processing on the gradient version of the image. Experimental results show that the proposed edge detection method achieved better performance than other state-of-the-art edge detection methods.

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