Target extraction from blurred trace infrared images with a superstring galaxy template algorithm |
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| Institution: | 1. School of Electronic and Information Engineering, Xi''an Jiaotong University, Xi’an, China;2. Ministry of Education Key Lab For Intelligent Networks and Network Security, Xi’an, China;3. Guang Dong Xi’an Jiaotong University Academy, Shunde, China;4. University of Toronto 27 King’s College Circle Toronto, Ontario M5S 1A1 Canada;5. School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 211111, China;6. National Engineering Lab for Big Data Analytics, Xi''an Jiaotong University, Xi’an, China |
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| Abstract: | Accurate and efficient targets extraction from blurred trace infrared images has very important meaning for latent trace evidence collection in crime scene. Based on the superstring theory, a superstring galaxy template extraction algorithm for infrared trace target is presented. First, all of the pixels are divided into three classes: target pixels, background pixels and blurred pixels. Next, the superstring template characteristics for every pixel in a blurred infrared image are calculated as the features of each pixel. Finally, a galaxy covering algorithm is proposed, target pixels and background pixels are used for training the galaxy covering domain of every galaxy classifiers, and these classifiers will divide each blurred pixel into two classes: a target pixel or a background pixel. Experimental results indicate that the superstring galaxy template algorithm can improve the target extraction rate and reduce the extraction error rate. |
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| Keywords: | Blurred infrared image Target extraction Superstring mapping Galaxy covering |
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