Image transition region extraction and thresholding based on local feature fusion

2013 ◽  
Vol 33 (1) ◽  
pp. 40-43 ◽  
Author(s):  
Tao WU ◽  
Junjie YANG
Keyword(s):  
Transition Region ◽  
Feature Fusion ◽  
Local Feature ◽  
Region Extraction

Lightweight feature fusion network design for local feature recognition of non-cooperative target

2020 ◽  
Vol 49 (7) ◽  
pp. 20200170
Author(s):  
徐云飞 Yunfei Xu ◽  
张笃周 Duzhou Zhang ◽  
王立 Li Wang ◽  
华宝成 Baocheng Hua
Keyword(s):  
Network Design ◽  
Feature Recognition ◽  
Feature Fusion ◽  
Local Feature

Exploiting Local Feature Fusion for Action Recognition

2016 ◽  
pp. 221-230
Author(s):  
Jie Miao ◽  
Xiangmin Xu ◽  
Xiaoyi Jia ◽  
Haoyu Huang ◽  
Bolun Cai ◽  
...  
Keyword(s):  
Action Recognition ◽  
Feature Fusion ◽  
Local Feature

Automatic Segmentation of Pores in Weld Images Based on Transition Region Extraction

2012 ◽  
Vol 217-219 ◽  
pp. 1964-1967
Author(s):  
Tong Tong ◽  
Yan Cai ◽  
Da Wei Sun ◽  
Peng Liu
Keyword(s):  
Transition Region ◽  
Automatic Segmentation ◽  
Experimental Results ◽  
Gray Level ◽  
Segmentation Method ◽  
Complex Environment ◽  
Weld Defects ◽  
Contrast Enhanced ◽  
Region Extraction ◽  
Low Pass

In allusion to the complex images of weld defects, weak contrast between the target and the background, a new segmentation method based on gray level difference transition region extraction is proposed. The paper analyzes the characteristic of weld defects, and then low-pass filtering and contrast enhanced are used to enhance the clarity. Finally, we extract the transition region and confirm a threshold for defects segmentation. The experimental results show that the method can extract the transition region more accurate, and segment the image much better in complex environment.

Sign in / Sign up

Export Citation Format

Share Document