Papers by Keyword: Hamming Distance

Abstract: Investigation of symbolic representations of environments plays an important role for solution of various problems of robot visual navigation. In this paper, we study methods of symbolic trajectory description for mobile robot navigation. For this purpose, we use the fresco approach. We consider the problem of salient frescoes selection. In particular, we consider various modifications of the Levenshtein distance method. Also, we use different circular strings methods.

Abstract: Splicing broken files played an important role in judicial evidence reconstruction, historical documents repair and military information obtainment and other fields. In this paper, we analyzed the reconstruction of broken pieces, which was modeled as an optimal matching problem. The Hamming distance was used as the matching degree of edge splicing. Firstly, we use the iterative threshold selection method to determine the gray scale threshold. Secondly, we chose the minimum summation of and as objective function. Then we use clustering analysis to classify the pieces into different lines, and selected the top and bottom position of the first line on each piece as decision variables. Finally, we took word width and column spacing into consideration and used row matching algorithm to splice lines into a complete image.

Abstract: Information of topology is significant for network planning and management in the Wireless Sensor Network (WSN). In this paper we propose a topology identification algorithm based on data fusion system in WSN. Firstly, the algorithm got the collections of approximate ancestors of each node according to the information of packet delay and/or packet loss. Secondly, it identifies parent-child relationship of the nodes by calculating the Hamming distance between the current node and approximate ancestors nodes; and infers the topology of the network layer by layer. It use end-to-end measurements and does not incur any additional burden on the network. NS2 simulation results show the high accuracy and efficiency of the proposed algorithm.

Abstract: Nowadays, automatic scoring is an important way of teaching and examinations. However, there is no existing research on automatic scoring for subjective item of database domain both at home and abroad. According to the characteristics of database domain, we construct database domain synonyms ontology and proposed a text similarity calculation algorithm based on Hamming distance. Then we implement the automatic scoring for subjective item of database domain on the basis of ontology. In addition, in order to verify the accuracy and rationality of the algorithm, we take a specific subject as an example. The experiment results further illustrate the accuracy and efficiency of the proposed automatic scoring algorithm.

Abstract: The complexity of map scenes of computer games has important influence to the degree of games difficulty, and it is also the key factor of pathfinding performance. In this paper, a kind of maps complexity metric index which based on the accumulation of xor is defined. The index calculates map complexity through accumulating the xor-value of each adjacent cells line by line. The experimental results demonstrates that the metric index is highly relative with the efficiency of A* and HPA* algorithm. It can provide reference for the design of game maps.

Abstract: Visual navigation is extensively used in contemporary robotics. In particular, we can mention different systems of visual landmarks. In this paper, we consider one-dimensional color panoramas. Panoramas can be used for creating fingerprints. Fingerprints give us unique identifiers for visually distinct locations by recovering statistically significant features. Fingerprints can be used as visual landmarks for mobile robot navigation. In this paper, we consider a method for automatic generation of fingerprints. Since a fingerprint is a circular string, different string-matching algorithms can be used for selection of fingerprints. In particular, we consider the problem of finding the consensus of circular strings under the Hamming distance metric.

Abstract: Currently Augmented Reality (AR) simply based on natural features is not efficient. In this paper, we propose a novel simple method of AR registration using Oriented FAST and Rotated BRIEF (ORB) features and Kanade-Lucas-Tracker (KLT) tracking algorithm. First we extract ORB natural features from a reference image and the first video frame. Select the matching points using appropriate Hamming distance and Random Sample Consensus (RANSAC) algorithm. Then we track the matched ORB features of the next video frames with an updating KLT strategy. Finally we calculate and determine the camera pose using the matched feature point sets. Our experiments show that, in the cases of different scales, different angles, some changes in ambient light, complex backgrounds or part of the reference image blocked, our AR system performs well to track and position accurately. And the processing speed of our system approximately meets the requirement of real-time system.

Abstract: To solve the problems of frame sync words gotten unstably and short frame synchronization state decision time, a new parallel frame synchronization scheme is presented. The proposed method improves the robustness and state decision performance of the frame synchronization system. The method is implemented and verified in a high-speed satellite communication system. Based on that practical application, a multi-channel parallel frame synchronization design method is given for even higher speed data communication systems.

Abstract: The Explicit Finite Difference (EFD) method is used for calculating the energy conservation equation during solidification. In order to improve the computational efficiency, the equivalent specific heat method is adopted to calculate the latent heat and the high order Alternating Direction Implicit (ADI) method is also applied, which is fourth order in space and second order in time. The degree of similarity between the simulation results and experimental results is analyzed quantitatively by the Hamming Distance (HD) for the first time, and results show that this high order mathematical model based on the equivalent specific heat method and the high order ADI method is faster and more accurate than the EFD method.

Abstract: The internal link loss characteristic inference has become an increasingly important issue for operating and evaluating a wireless sensor network. In this paper we propose a new algorithm, based on MPLE algorithm and binary hamming distance and hop count, to infer the internal link loss characteristics. First, we use the MPLE model to part the problem of inference into the serial of sub-problem, a sub-problem is compose of subtree that contain two leaf nodes. Then, we select the subtree by using hamming distance of the sequences at each pair of nodes and incorporating the hop count available at each node in WSN. finally the Pseudo-Likelihood Function (PLF) is used to solve the problem. The simulation shows that the link loss performance parameters can be inferred accurately, and the proposed algorithm scales well according to the sensor network size.