Varieties of trusted computing products usually follow the mechanism of liner-style chain of trust according to the specifications of TCG.The distinct advantage is that the compatibility with the existing computing pl...Varieties of trusted computing products usually follow the mechanism of liner-style chain of trust according to the specifications of TCG.The distinct advantage is that the compatibility with the existing computing platform is preferable,while the shortcomings are obvious simultaneously.A new star-style trust model with the ability of data recovery is proposed in this paper.The model can enhance the hardware-based root of trust in platform measurement,reduce the loss of trust during transfer process,extend the border of trust flexibly,and have the ability of data backup and recovery.The security and reliability of system is much more improved.It is proved that the star-style trust model is much better than the liner-style trust model in trust transfer and boundary extending etc.using formal methods in this paper.We illuminate the design and implementation of a kind of trusted PDA acting on star-style trust model.展开更多
The scale invariant feature transform （SIFT） feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in m...The scale invariant feature transform （SIFT） feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in many applications, such as object recognition, video tracking, and gesture recognition. However, in noisy and non-rigid object recognition applications, especially for infrared human face recognition, SIFT-based algorithms may mismatch many feature points. This paper presents a star-styled window filter-SIFT （SWF-SIFT） scheme to improve the infrared human face recognition performance by filtering out incorrect matches. Performance comparisons between the SIFT and SWF-SIFT algorithms show the advantages of the SWF-SIFT algorithm through tests using a typical infrared human face database.展开更多
基金Supported by the National Natural Science Foundation of China(61303024)the Natural Science Foundation of Hubei Province(2013CFB441)+1 种基金the Foundation of Science and Technology on Information Assurance Laboratory(KJ-13-106)the Natural Science Foundation of Jiangsu Province(BK20130372)
文摘Varieties of trusted computing products usually follow the mechanism of liner-style chain of trust according to the specifications of TCG.The distinct advantage is that the compatibility with the existing computing platform is preferable,while the shortcomings are obvious simultaneously.A new star-style trust model with the ability of data recovery is proposed in this paper.The model can enhance the hardware-based root of trust in platform measurement,reduce the loss of trust during transfer process,extend the border of trust flexibly,and have the ability of data backup and recovery.The security and reliability of system is much more improved.It is proved that the star-style trust model is much better than the liner-style trust model in trust transfer and boundary extending etc.using formal methods in this paper.We illuminate the design and implementation of a kind of trusted PDA acting on star-style trust model.
文摘The scale invariant feature transform （SIFT） feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in many applications, such as object recognition, video tracking, and gesture recognition. However, in noisy and non-rigid object recognition applications, especially for infrared human face recognition, SIFT-based algorithms may mismatch many feature points. This paper presents a star-styled window filter-SIFT （SWF-SIFT） scheme to improve the infrared human face recognition performance by filtering out incorrect matches. Performance comparisons between the SIFT and SWF-SIFT algorithms show the advantages of the SWF-SIFT algorithm through tests using a typical infrared human face database.
