Application Research of Image Matching Based on Morphology Description Matrix and Genetic algorithm

2009 ◽  
Author(s):  
Yang Wenli ◽  
Zeng Zhiyuan
Keyword(s):  
Genetic Algorithm ◽  
Image Matching ◽  
Application Research

Low-Altitude Airship Remote Sensing Images Matching Based on Improved Hybrid Ant Colony Algorithm

2012 ◽  
Vol 532-533 ◽  
pp. 924-928
Author(s):  
Bang Long Pan ◽  
Wei Ning Yi ◽  
Xian Hua Wang
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithm ◽  
Data Processing ◽  
Image Matching ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Neighborhood Search ◽  
Registration Process ◽  
Low Altitude ◽  
Image Pairs

Low-altitude unmanned airship remote sensing is attractive to various applications. However, at present, since the airship is bulky, weak to resist wind, unstable to flight attitude, and can not be equipped with specialized remote sensing sensors, image data processing is confronted with new challenges when traditional data processing methods are used. In this paper, improved hybrid ant colony algorithm (HACA), a new image matching method, is proposed. Firstly we perform a pre-registration process that roughly aligns the image pairs by GPS/electronic compass geolocation. Once the pre-registration is completed, a fine-scale registration process is executed by applying a hybrid algorithm of genetic algorithm (GA) and ant colony algorithm (ACA) based on neighborhood search strategy that is detected by the linear quadtree Morton coding. The image pairs are then matched by using optimal solution obtained from the automatic updates of ant colony pheromone. By compared with traditional genetic algorithm and ant colony algorithm, the improved HACA results show that search calculation time is increased by the maximum 406℅, standard root mean square error of image matching by the best 235℅. The experiment result proves that improved HACA exactly provides an effective method for image matching. The local maxima of the function can be avoided efficiently and search speed of the global optimum is increased greatly.

Robot View Navigation Based on Level-Divided Strategy

2013 ◽  
Vol 753-755 ◽  
pp. 3108-3111
Author(s):  
Yin Bing Li
Keyword(s):  
Genetic Algorithm ◽  
Real Time ◽  
Image Matching ◽  
Search Strategy ◽  
Detection Algorithm ◽  
Adaptive Genetic Algorithm ◽  
Exact Matching ◽  
Matching Accuracy ◽  
Similarity Detection ◽  
Time Requirements

In allusion to the colored image matching characteristic in the system of robot view navigation, SSDA (the sequential similarity detection algorithm) is improved and adaptive genetic algorithm is brought in; meanwhile, level-divided search strategy connective with rough and exact matching. The improved algorithm can enhance the image matching speed with no matching accuracy reduced, so that real-time requirements of robot view navigation can be met and robot view navigation will be of preferable robustness.

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