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Search Results: 1 - 10 of 60671 matches for " ZHAO Chun-xia "
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Road Detection and Corner Extraction Using High Definition Lidar
Xia Yuan,Chun-Xia Zhao,Hao-Feng Zhang
Information Technology Journal , 2010,
Abstract: In this study, we propose an algorithm to detectro and find landmarks (corners) in 3-D point cloud. Point cloud classification is an approach to find road or specific target but it is usually a time-consuming task especially when theory of random field was introduced into this research area recent years. The proposed algorithm is adapted for fast preprocessing and its parameters don’t need online learning. The algorithm employs a fuzzy cluster method based on maximum entropy theory to segment points, then a multi-times weight least-square linear fitting algorithm is used to differentiate linear and nonlinear distributed point segment. We extract road surface instead of road boundary and filters are designed to find road area. A corner fitting method will find corners of buildings as land marks according to different distribution of points. The spatial dependences among different laser detectors are considered to refine the results of extracted features. Experiment results valid the algorithm. The algorithm successfully extracts road and corners of buildings in point cloud which is sampled from complex semi-structured environment.
Lidar Scan-Matching for Mobile Robot Localization
Xia Yuan,Chun-Xia Zhao,Zhen-Min Tang
Information Technology Journal , 2010,
Abstract: Problem of mobile robot localization is usually solved by using GPS and INS system, but the system error of this kind of system has to be corrected by other sensors such as lidar. This study proposes an algorithm to do lidar scan-matching. The method employs a fuzzy clustering algorithm to segment points of lidar scans first and then do weight least-square linear fitting for each segment. Segments that satisfy linear distributed are picked out to calculate rotation between two lidar scans. Then the algorithm computes translation by calculating shifting of matched points. A principle called matching-range-point rule is used to find matching points belong to two scans. The characteristic of this proposed method it abandons iteration when calculate rotation and translation. It works fast and reliably and adapts to correct the error of GPS and INS system to localize a mobile robot accurately.
Visual Features Fusion for Scene Images Classification
GAO Hua,ZHAO Chun-xia,ZHANG Hao-feng
Lecture Notes in Engineering and Computer Science , 2012,
Automatic Pavement Crack Detection Using Texture and Shape Descriptors
HU Yong,ZHAO Chun-xia,WANG Hong-nan
IETE Technical Review , 2010,
Abstract: Pavement distress detection and analysis is the most important part of automated pavement -inspection -systems. Due to the circumstances such as complex texture, uneven illumination, and nonuniform -background, pavement distress detection is not a simply edge detection process. Over the past 30 years, lots of methods were proposed to detect pavement distresses, especially cracks. In this letter, a novel automatic pavement crack detection approach based on texture analysis and shape descriptors is proposed. Pavement surface is seen as a texture surface, and distresses are defined as inhomogeneities occurring in the texture surface. Six texture features and two translation-invariant shape descriptors were used here as discriminate features against irregular texture and uneven illumination. By using a SVM classifier, all sub-images are classified as crack or non-crack. Final results were obtained after post-processing, which includes segmentation, fake-crack eliminating, and crack-measuring methods. Compared with a traditional edge detector such as a Canny operator, experimental results demonstrated that all cracks are correctly detected by the proposed method, even in a strong texture background or in the surface with uneven illumination.
Terrain Classification Based on Gaussian Mixture Model for Unstructured Complicated Environment

HAN Guang ZHAO Chun-xia YUAN Xia,

计算机科学 , 2009,
Abstract: A terrain classification algorithm based on Gaussian Mixture Model for unstructured complicated environment was proposed,considering color shift due to weather changing,illumination variety,reflectance spectrum blurring of similar terrain,such as soil and sand.First,terrain feature in different illumination conditions as training data were computed.This feature is one fusion feature of texture feature of improved Discrete Cosine Transform and YIQ color feature.Then the Gaussian Mixture Model was trained by ...
A Stereo Matching Algorithm Using Dynamic Programming and Left-right Consistency

ZHANG Hao-feng,ZHAO Chun-xia,

中国图象图形学报 , 2008,
Abstract: Stereo matching is one of the most important researches in computer vision.In order to obtain dense and correct disparity,a stereo matching algorithm using dynamic programming and left-right consistency is presented.Firstly,the left and right disparity space images are computed using the left and right images as basic image separately.Secondly,in the computed disparity space images,the disparity images are computed using dynamic programming.Then the left-right consistency of the disparity images is used to remove the mismatching pixels,and to generate the part of near real disparity images.At last,according to the ordering constraint of disparity image,a method detecting the searching space of unmatched pixels is presented.And an ordinary but efficient strategy is proposed to finalize these pixels.The experiments on some standard stereo pairs are executed,and the results show the algorithm is effective.
Particle swarm optimization based on endocrine regulation mechanism

CHEN De-bao,ZHAO Chun-xia,

控制理论与应用 , 2007,
Abstract: Motivated by high-level regulation principle of endocrine system, a particle swarm optimization based on endocrine regulation mechanism is put forward. First, emotional evaluation method is designed combining with the best fitness, average fitness and local fitness of particles in current generation, and emotion in next generation is evaluated. Then, the behaviors of particles in next generation are updated by interaction of neural and endocrine systems, and momentum factor is used to reduce the probability of local convergence. The convergence of algorithm is analyzed, and the effectiveness is demonstrated by optimization experiments of typical functions and path planning.
Geographic Routing Algorithm Based on Link Quality in Mobile Ad-hoc Networks

HONG Lei,HUANG Bo,ZHAO Chun-xia,

计算机科学 , 2011,
Abstract: How to implement the simple routing mechanism enables nodes transfer the packets efficiently within a shorter time is a basic problem in research of the mobile Ad-hoc networks. According to the deficiencies of high bit error rates and anti interference technique, link quality was proposed as the new metric for route selection and a geographic routing algorithm based on link duality called LQPR was designed and implemented in this paper which solves the problem of a downward trend of packet delivery ratio on Non-ideal wireless link by using traditional greedy algorithm. The LQPR algorithm, which combines the LQ mode and Perimeter mode, guides data forwarding by use of the geographic information obtained by the location techniques, which has such advantages as less control overhead, optimal path selection and efficient transmission. The proposed routing protocol LQPR was simulated by NS-2. Through evaluating and comparing the result in term of average end-to-end delay, aggregate throughput and delivery success rate, the validation of LQPR was then carried out with simulating data.
Novel FastSLAM algorithm based on square root unscented Kalman filter

LV Tai-zhi,ZHAO Chun-xia,

计算机应用研究 , 2012,
Abstract: Standard FastSLAM algorithm suffers from particle set degeneracy and accumulation errors caused by linearization of the nonlinear model. To overcome the above problems, this paper proposed a novel FastSlam algorithm based on square root unscented Kalman filterSR-UKF. SR-UKF selected a group of representative sigma points to approximate the covariance, these sigma points were propageted through the non-linearforce model to reconstruct the new statistical characteristics. Using SR-UKF to replace EKF for posteriori estimation of particles could reduce the linearization error and slow down particle set degeneracy. SR-UKF ensured the non-negative definite of covariance matrix to guarantee the stability of SLAM algorithm. The simulation experiments demonstrate that the proposed algorithm is better than FastSLAM 2. 0 both in accuracy and robustness.
Xue-Wen Zhu,Xu-Zhao Yang,Chun-Xia Zhang,Gang-Sen Li
Acta Crystallographica Section E , 2009, DOI: 10.1107/s1600536809040495
Abstract: In the title complex, [ZnI2(C14H19N3O3)], the ZnII atom is four-coordinated by the imine N and phenolate O atoms of the Schiff base ligand, and by two iodide ions in a distorted tetrahedral coordination. In the crystal structure, molecules are linked through intermolecular N—H...O hydrogen bonds, forming dimers.
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