The effects of anisotropic Gaussian diffusion in scale invariant feature detection

Author(s):  
Warner Skoch ◽  
John Gauch
2018 ◽  
Vol 7 (2.8) ◽  
pp. 42
Author(s):  
D Rajasekhar ◽  
T Jayachandra Prasad ◽  
K Soundararajan

Feature detection and image matching constitutes two primary tasks in photogrammetric and have multiple applications in a number of fields. One such application is face recognition. The critical nature of this application demands that image matching algorithm used in recognition of features in facial recognition to be robust and fast. The proposed method uses affine transforms to recognize the descriptors and classified by means of Bayes theorem. This paper demonstrates the suitability of the proposed image matching algorithm for use in face recognition appli-cations. Yale facial data set is used in the validation and the results are compared with SIFT (Scale Invariant Feature Transform) based face recognition approach.


2007 ◽  
Author(s):  
Jian Gao ◽  
Xinhan Huang ◽  
Gang Peng ◽  
Min Wang ◽  
Xinde Li

2013 ◽  
Vol 347-350 ◽  
pp. 3469-3472 ◽  
Author(s):  
Wei Wu ◽  
Sen Lin ◽  
Hui Song

Compared with the traditional method of contact collection, contactless acquisition is the mainstream and trend of palm vein recognition. However, this method may lead to image deformation caused by no parallel of the palm plane and the sensor plane. In order to improve the limited effect of Scale Invariant Feature Transform (SIFT) about this problem, a better method of palm vein recognition which based on principle line SIFT is proposed. Based on the self-built database, this method is compared with the SIFT and other typical palm vein recognition methods, the experimental results show that our system can achieve the best performance.


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