scholarly journals Improved Offline Signature Verification Scheme Using Feature Point Extraction Method

2008 ◽  
Vol 4 (2) ◽  
pp. 111-116 ◽  
Author(s):  
Debasish Jena ◽  
Banshidhar Majhi ◽  
Sanjay Kumar Jena
Keyword(s):  
Extraction Method ◽  
Feature Point ◽  
Signature Verification ◽  
Verification Scheme ◽  
Feature Point Extraction ◽  
Offline Signature Verification

A feature point extraction method based on the continuity of laser stripe pixels

2016 ◽  
Author(s):  
Na Wang ◽  
YiKun Zhang ◽  
Hao Chen ◽  
Kai Wang ◽  
Hui Xia
Keyword(s):  
Extraction Method ◽  
Feature Point ◽  
Laser Stripe ◽  
Feature Point Extraction

Self-adaptative variable-metric feature point extraction method

2017 ◽  
Vol 25 (1) ◽  
pp. 188-197 ◽  
Author(s):  
屈玉福 QU Yu-fu ◽  
刘子悦 LIU Zi-yue ◽  
江云秋 JIANG Yun-qiu ◽  
周 丹 ZHOU Dan ◽  
王一帆 WANG Yi-fan
Keyword(s):  
Extraction Method ◽  
Feature Point ◽  
Variable Metric ◽  
Feature Point Extraction

Feature Point Extraction Method of X-Ray Image Based on Scale Invariant

2013 ◽  
Vol 274 ◽  
pp. 667-670
Author(s):  
Yan Wei Wang ◽  
Si Qing Zhang ◽  
Bing Lin ◽  
Hong Liang ◽  
Yan Ming Pan
Keyword(s):  
Extraction Method ◽  
Quadratic Function ◽  
Feature Point ◽  
Scale Transformation ◽  
Gaussian Kernel ◽  
Scale Invariant ◽  
Low Contrast ◽  
X Ray ◽  
Feature Point Extraction ◽  
Key Points

Feature Point Extraction Method of X-ray Image Based on Scale Invariant is proposed in this paper for industrial X-ray image with low contrast and some artifacts. First of all, the scale transformation of original image is adopted by the Gaussian kernel to building the DOG multi-scale pyramid. Then, the location and scale of the key points is fixed by the three-dimensional quadratic function. Finally, the Simply SIFT descriptor illustrates the key points. Experimental results show that the algorithm has good stability in translation, rotation and affine transformation, especially with 10 percent normalized Gaussian noise, this algorithm can still be detected feature points accuracy.

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