A SIFT feature based registration algorithm in automatic seal verification

Jin He; Xuewen Ding; Hao Zhang; Tiegen Liu

doi:10.1117/12.999384

30 November 2012 A SIFT feature based registration algorithm in automatic seal verification

Jin He, Xuewen Ding, Hao Zhang, Tiegen Liu

Proceedings Volume 8558, Optoelectronic Imaging and Multimedia Technology II; 85581R (2012) https://doi.org/10.1117/12.999384
Event: Photonics Asia, 2012, Beijing, China

Abstract

A SIFT (Scale Invariant Feature Transform) feature based registration algorithm is presented to prepare for the seal verification, especially for the verification of high quality counterfeit sample seal. The similarities and the spatial relationships between the matched SIFT features are combined for the registration. SIFT features extracted from the binary model seal and sample seal images are matched according to their similarities. The matching rate is used to define the similar sample seal that is similar with its model seal. For the similar sample seal, the false matches are eliminated according to the position relationship. Then the homography between model seal and sample seal is constructed and named H_S . The theoretical homography is namedH . The accuracy of registration is evaluated by the Frobenius norm of H-H_S . In experiments, translation, filling and rotation transformations are applied to seals with different shapes, stroke number and structures. After registering the transformed seals and their model seals, the maximum value of the Frobenius norm of their H-H_S is not more than 0.03. The results prove that this algorithm can accomplish accurate registration, which is invariant to translation, filling, and rotation transformation, and there is no limit to the seal shapes, stroke number and structures.

Citation Download Citation

Jin He, Xuewen Ding, Hao Zhang, and Tiegen Liu "A SIFT feature based registration algorithm in automatic seal verification", Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85581R (30 November 2012); https://doi.org/10.1117/12.999384

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available