Cognitive radio is a kind of intelligent and spectrum sharing technology for improving the utilization of spectrum. It can
detect primary user by sensing empty spectrum bands. Due to shadowing and multi-path fading, the reliability of single
terminal detection is low. Information fusion algorithm based on collaborative spectrum sensing can improve the sensing
performance significantly. In this paper, a high performance information fusion algorithm has been studied on the basis
of analyzing several classic fusion algorithms. We drive the expression for the probability of the detection and the falsealarm
for this fusion algorithm. Simulating results indicate that the fusion algorithm presented in this paper achieves
better detection performance than traditional fusion algorithms.
In the researching field of content based image retrieval (CBIR), shape features based is the most difficult to deal with.
The shape features are the most significant characteristics comparing with other lower basic image features and they are
the hardest features to describe. In this paper, one method is presented to describe the features by adopting MPEG-7
standard recommend Fourier descriptor after the object shape features extracted by adaptive threshold segmentation.
Choose the Fourier transformed border function to be shape descriptor. Use curvature scale function to represent shape
features. Experiments show that image shape features extraction method used in this paper is accurate in edge location
and will further facilitate the description of shape features. Meanwhile the use of MPEG-7 Fourier descriptors can
express shape characteristics that contain abundant information with less data.