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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44221

Title: Novel aircraft type recognition with learning capabilities in satellite images
Authors: Jun-Wei Hsieh
Jian-Ming Chen
Chi-Hung Chuang
Kao-Chin Fan
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Image recognition
Military aircraft
Time factors
Environmental factors
Military satellites
Pollution
Security
Image processing
Image quality
Feature extraction
Date: 2004-10
Issue Date: 2017-11-16T01:56:57Z
Publisher: 2004 IEEE International Conference on Image Processing
Abstract: Abstract:The collection of satellite images is not constrained by time and can be captured day and night. It is unlike the images captured by aircrafts which are heavily constrained by weather conditions and environmental factors to secure useful images. Recently, satellite images have been widely applied in many fields, such as resource mining, pollution monitoring, etc. In this paper, we plan to apply it to the military to analyze different types of aircrafts for security purpose. In our system, image processing techniques are first employed to perform the image preprocessing tasks, such as image quality enhancement, noise removal, rotation, scaling, and translation adjustment. Then, distinguishable features are extracted from aircrafts for recognition. Last, a multi-level recognition scheme is adopted for recognizing the types of aircrafts by incorporating suitable weight into each recognition level. Experimental results reveal the feasibility and validity of the proposed approach in recognizing aircrafts in satellite images.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44221
Appears in Collections:[資訊工程學系] 演講及研討會

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