In order to improve the accuracy of identification and localization of cell microorganisms by optical micropositioning system, on the one hand, the hand-eye calibration method should be optimized, on the other hand, the accuracy of global image recognition should be improved. Aiming at those, a two-step method for hand-eye calibration of the system was proposed. Firstly, the origin of the system was determined by calibrating the fixed target, and the transformation relationship of the vision module to the origin of the system was obtained. Then, according to the starting point position of each photograph, the number of photoing and the step size of movement, the transformation relationship of the global image to the origin of the system was solved. Finally, in order to further improve the accuracy of the global transformation relationship, an error correction method based on Fourier transform was used to obtain the error of the visual module in movement,then the error was added into the system for compensation. Experimental results show that after error compensation, the micropositioning system has the error mean value in X-axis direction reduced from 10.23 μm to -0.002 μm, the error mean value in Y-axis direction reduced from 6.9 μm to -0.50 μm, and the average positioning accuracy over 99%. The results show that the proposed method can be applied to the optical micropositioning system for high-precision automated capture of cell microorganisms.

The extraction of multi-view matching points is one of the key problems in 3D reconstruction of multi-view image scenes, and the accuracy of the reconstruction will be affected directly by the extraction result. The extraction problem of multi-view matching points was converted into the dynamic connectivity problem and a Union-Find (UF) method was designed. The nodes of UF were organized using efficient tree structure in which parent-link connection was adopted. In the process of increasing the matching points, only the addressing parameters of a single node needed to be modified, which avoided comparing the calculation process of the addressing parameters through traversing the array, and the efficiencies of locating and modifying were improved. A weighting strategy was used to optimize the algorithm, and the weighted encoding method was used to replace the conventional hard encoding, which could balance the structure of the tree and reduce the average depth of the dendrogram. The experimental results of multiple image sets show that the proposed algorithm based on UF can extract more multi-view matching points, and is more efficient than the conventional Breadth-First-Search (BFS) algorithm.

To solve the problems of synchronization error accumulation and unbalanced energy consumption in multi-hop wireless sensor networks, a cluster-based and energy-balanced time synchronization algorithm for wireless sensor networks was proposed. Based on hierarchical clustering topology, cluster heads in adjacent layers adopted pairwise broadcast mechanism instead of bidirectional pair-wire synchronization mechanism to reduce communication overhead and the synchronization error of transmission delay. Cluster members synchronized the cluster head using the combination of bidirectional pair-wise synchronization and reference broadcast synchronization. In addition, the response node was selected according to residual energy to balance energy consumption of cluster nodes. The performance of synchronization precision and energy consumption of the proposed algorithm and traditional algorithm were analyzed by theoretical analysis and simulation. The results show that the new algorithm not only ensures high synchronization accuracy, but also reduces communication overhead and balances network node energy consumption to lengthen the cycle life of the network.

As a kind of pure location routing algorithm in Wireless Multimedia Sensor Network (WMSN), Two Phase Geographic Greedy Forwarding (TPGF) helps to select the next-hop node which is of nearest distance to the destination from neighbor ones. In some cases, the distance between the next-hop node and the destination node could be farther than that of the current node and the destination node; At the same time, by numbering the nodes, TPGF solves the problem of hole and satisfies the Quality of Service (QoS) requirements. In line with the strategy of selecting the next-hop node farther than the current node, action-angle variables and DATF (Direction-Angle Greedy Forwarding) algorithm were introduced to guarantee and optimize the process of selecting the bound nodes. The simulation result indicates that DATF algorithm shows better performance than TPGF in both energy consumption and end-to-end transmission delay and also has a significant effect on solving the problem of hole.

Color coded structured light based on De Bruijn sequence is a kind of spatial code method that is characterized by rapid shape measurement. The recognition of color stripes is a key issue. Considering projected De Bruijn stripe pattern combining four colors with high and low intensity, segmentation of high and low intensity stripes was implemented by using linear filter of second derivative of L channel in L*a*b* color space. Adaptive color clustering was designed by employing Principal Component Analysis (PCA) and K-means clustering. The recognition of four colors with two intensities was finished. The experimental results indicate that the proposed method is robust to factors such as ambient light and it satisfies demand for high precision and simple extraction of information to structured light vision measurement.

In order to ensure system security and reflect availability in authorization management, a method for querying authorization was proposed based on solvers for partial maximal satisfiability problem. Static authorization descriptions and dynamic mutually exclusive constraints were translated into hard clauses. The algorithm was adopted to update hard clauses and translate requested permissions into soft clauses. Soft clauses were effectively encoded, and the recursive algorithm was utilized to satisfy all hard clauses and as many soft clauses as possible. The experimental results show that the method can ensure system security, it follows the least privilege principle, and the query efficiency outperforms solvers for maximal satisfiability problem.

Only using estimation of leading edge for target will cause vertical and horizontal ambiguity. Therefore, a new method of Synthetic Aperture Radar (SAR) target aspect estimation based on Radon transform of leading edge was proposed. The new method was introduced to eliminate the ambiguity of horizontal and vertical aspect estimation based on the length of the target region. It is difficult to separate the long leading edge from the short one. By introducing the discrimination rule of the target leading edge, the problem that many traditional algorithms try to settle was solved due to the estimation algorithm of Radon transform. The experimental results on the MSTAR data prove the precision and robustness of the algorithm.

A method based on the omnivision was studied for the selflocation of mobile robot. According to optical principle, the omnivision sensor was designed. By using the omnivision sensor, robots panoramic image in working environment was obtained. With the aid of noise reduction, color threshold segmentation and center point computation and so on, the landmarks in the panoramic image were recognized. By using triangulation method, the robots position was obtained, which was a good basis for the navigation and the collision of robot. Experimental results prove that the method is feasible for the selflocation of mobile robot.