Wang Weizhi

Moving shadow detection based on Susan algorithm

In Intelligent Transportation Systems, moving shadows have always been wrongly detected as foreground objects, thus causing bad effect on the latter targets tracking and identify. In order to subtract the shadows lie in different circumstances,there has put forward a method of moving shadow detection based on Image edge detection which using Susan algorithm[9]. After getting the background with mixture Gaussian distribution, the moving foreground position can be accurately obtained via the background subtraction method, then use the Susan algorithm to detect the image edge in interested area. Finally, do shodow detection by analyzing the statistic characteristics of edge pixels. According to the experiment, this method is easy to operate and possesses high rate of accuracy, low rate of complexity, and well adapt to different kinds of shoadow distribution.

Automatic separation of overlapping objects

This paper presents an algorithm based on mathematical morphology to separate overlapping objects automatically, which locates their linking points by the distance transform and dilation. It develops the design and implementation of the approach. In particular, it applies the technique to the problem of separating liver cells in hepatitis pathology images. The experiments show that the technique is fast and the separated results are satisfactory.

Automatic Recognition Algorithm of Traffic Signs in Road Tunnel

We conduct feature extraction and feature selection of the pattern of traffic signs based on environmental characteristics of the road tunnel, and the color and shape information of traffic signs, then further accomplish multi-level classification of traffic signs using decision tree method. The method proposed in this paper based on decision tree classification algorithm can convert a complex multi-class problem into several simple classifications. Experimental results show that the algorithm has good recognition results.

A method of feature selection based on Particle Swarm Optimization algorithm with trans-gene operator

The purpose is to apply the binary particle swarm optimization (BPSO) in feature selection. According to feature selection, the method of particles coding, fitness functions, and feature selection functions were designed. Furthermore, trans-gene operator was adopted to solve BPSOpsilas premature convergence. The simulation experiment results show that the feature subsets selected by this new algorithm are representative. The conclusion is that this algorithm is available and feasible in feature selection.

The research of synergetic algorithm in intelligent control of crystal growth

This paper discusses the problem of multilevel control in an intelligent control system, and presents an intelligent control system of crystal growth. The synergetic algorithm in system identification is proposed.

The principle and application of synergetic pattern recognition

The paper first expounds the principle of synergetic pattern recognition. Then it discusses the implementation techniques of the pathology image classification system based on the principle in detail. Whats more, to resolve the problem that the synergetic neural network is weak in recognizing new test samples, it presents the information superposition self-learning algorithm based on a genetic algorithm. The experimental results prove the effectivity of the algorithm.