Lane recognition system based on the high-speed pattern matching method

2004 ◽  
Vol 35 (8) ◽  
pp. 45-53
Author(s):  
Yoshiki Ninomiya ◽  
Arata Takahashi ◽  
Mitsuhiko Ohta
Keyword(s):  
Pattern Matching ◽  
High Speed ◽  
Recognition System ◽  
Matching Method ◽  
Lane Recognition

scholarly journals A Novel Inertial-Aided Star Pattern Matching Method for Distributed Multiple FoVs

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Rong Wang ◽  
Yuxuan Cao ◽  
Jianye Liu ◽  
Zhi Xiong
Keyword(s):  
Pattern Matching ◽  
High Speed ◽  
Estimation Method ◽  
Line Of Sight ◽  
Measurement Information ◽  
Star Sensor ◽  
Matching Method ◽  
Inertial Measurement ◽  
Star Pattern ◽  
Vector Estimation

An aerospace vehicle in high-speed flight involves distributed multiple fields of view (FoVs) of a star sensor, and the maneuvering of the vehicle requires inertial-aided star pattern matching. Accordingly, an inertial-aided star pattern matching method for distributed multiple FoVs is proposed. First, the observation and fusion principles of distributed multiple FoVs are illustrated. Then, an inertial-aided star pattern matching scheme is designed based on the space-time distribution of the line-of sight (LoS) vector and inertial measurement information. Next, an LoS vector estimation method assisted by inertial information and the dynamic establishment of a distributed local catalog are proposed. Finally, in a simulation, the dynamic establishment of the part catalog improves the efficiency of star pattern matching by reducing the catalog scale, and the usability of inertial-aided star pattern matching is analyzed for different gyro and accelerometer precisions.

Text pattern matching based on a high-speed signal processor

1994 ◽  
Vol 30 (11) ◽  
pp. 837 ◽  
Author(s):  
P.A. Mitkas ◽  
S.P. Sastry
Keyword(s):  
Pattern Matching ◽  
High Speed ◽  
Signal Processor

scholarly journals A novel optimal multi-pattern matching method with wildcards for DNA sequence

2021 ◽  
Vol 29 ◽  
pp. 115-124
Author(s):  
Xinlu Wang ◽  
Ahmed A.F. Saif ◽  
Dayou Liu ◽  
Yungang Zhu ◽  
Jon Atli Benediktsson
Keyword(s):  
Dna Sequence ◽  
Pattern Matching ◽  
Health Informatics ◽  
State Of The Art ◽  
Machine Language ◽  
Data Sets ◽  
Fundamental Issue ◽  
Matching Method ◽  
Dna Sequence Alignment ◽  
The Given

BACKGROUND: DNA sequence alignment is one of the most fundamental and important operation to identify which gene family may contain this sequence, pattern matching for DNA sequence has been a fundamental issue in biomedical engineering, biotechnology and health informatics. OBJECTIVE: To solve this problem, this study proposes an optimal multi pattern matching with wildcards for DNA sequence. METHODS: This proposed method packs the patterns and a sliding window of texts, and the window slides along the given packed text, matching against stored packed patterns. RESULTS: Three data sets are used to test the performance of the proposed algorithm, and the algorithm was seen to be more efficient than the competitors because its operation is close to machine language. CONCLUSIONS: Theoretical analysis and experimental results both demonstrate that the proposed method outperforms the state-of-the-art methods and is especially effective for the DNA sequence.

scholarly journals Handwritten tifinagh character recognition using simple geometric shapes and graphs

2019 ◽  
Vol 13 (2) ◽  
pp. 598
Author(s):  
Youssef Ouadid ◽  
Abderrahmane Elbalaoui ◽  
Mehdi Boutaounte ◽  
Mohamed Fakir ◽  
Brahim Minaoui
Keyword(s):  
Character Recognition ◽  
Graph Matching ◽  
Recognition Rate ◽  
Recognition System ◽  
Features Extraction ◽  
Experimental Results ◽  
Feature Points ◽  
Matching Method ◽  
Extraction Algorithm ◽  
Novel Algorithm

<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

scholarly journals Research on the Relative Positions-Constrained Pattern Matching Method for Underwater Gravity-Aided Inertial Navigation

2015 ◽  
Vol 68 (5) ◽  
pp. 937-950 ◽  
Author(s):  
Lin Wu ◽  
Hubiao Wang ◽  
Hua Chai ◽  
Houtse Hsu ◽  
Yong Wang
Keyword(s):  
South China Sea ◽  
Pattern Matching ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Success Rates ◽  
Simulation Test ◽  
Matching Method ◽  
Contour Matching ◽  
Simulation Results ◽  
Straight Lines

A Relative Positions-Constrained pattern Matching (RPCM) method for underwater gravity-aided inertial navigation is presented in this paper. In this method the gravity patterns are constructed based on the relative positions of points in a trajectory, which are calculated by Inertial Navigation System (INS) indications. In these patterns the accumulated errors of INS indicated positions are cancelled and removed. Thus the new constructed gravity patterns are more accurate and reliable while the process of matching can be constrained, and the probability of mismatching also can be reduced. Two gravity anomaly maps in the South China Sea were chosen to construct a simulation test. Simulation results show that with this RPCM method, the shape of the trajectory in gravity-aided navigation is not as restricted as that in traditional Terrain Contour Matching (TERCOM) algorithms. Moreover, the performance included matching success rates and position accuracies are highly improved in the RPCM method, especially for the trajectories that are not in straight lines. Thus the proposed method is effective and suitable for practical navigation.

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