Classing object is an important step for the high-level visions processing tasks, such as security managing, and
abnormality event analysis etc. In this paper, we address these challenges in real-world unconstrained environments
where the background is complex and dynamic. In the algorithm proposed, we extract the features in a color space
technique is also developed to monitor the abnormal surface of water based on Mutation Particle Swarm Optimization
(MPSO). Our know, MPSO is one of the important evolutionary algorithms that it not only makes use of a mutation
operator to update particles/individuals which was originally designed for Genetic Algorithm (GA), but also a weighted
update rule can produce the new swarm for MPSO. Experimental results show that our algorithm works efficiently and
In this paper, we propose a method to find out the intrinsic parameters of the camera using the matrix rank constrain (MRC) of the relation matrix for absolute conic W. At the end of this paper, experimental results are presented and are compared with the other methods, which show the good performance of this proposed method.
In this paper, we propose a new method for segmenting the moving objects in the difference image sequence, using the adaptive invariable moments (AIM). After detecting and segmenting the moving objects, we propose an analysis method of the moving objects’ trajectories, speeds and accelerations. The experiment results show that these methods are robust and effective.
In this paper, we propose a new method to detecting the moving objects using the orthogonal Guassian-Hermite moments. For the segmentation of moving objects in the moment images, we propose the fuzzy relation method (FRM) and 3D morphological relaxation method (3DMRM). Finally, we analyze the trajectories, speeds and accelerations of moving objects; determining moving direction of moving objects. The experiment results are reported, which show the robustness of our methods.
In this paper, we analyze some properties of the orthogonal Gaussian-Hermite moments and propose a new method to detect the moving objects using the orthogonal Gaussian-Hermite moments. For the segmentation of moving objects in such moment images, we propose the fuzzy relaxation method (FRM) and 3D morphological relaxation method (3DMRM). The experiment results are reported, which show the robustness of our methods.