Title :
The Model of Visual Attention Infrared Target Detection Algorithm
Author :
Tingjun, Li ; Fuguang, Zhang ; Xinju, Cai ; Qilai, Huang ; Qiang, Guo
Author_Institution :
Naval Aeronaut. & Astronaut. Univ., Yantai, China
Abstract :
The model of visual attention infrared target detection algorithm is presented. Mainly the visual features are extracted from the brightness contrast and movement in the current frame still images and image sequences of the motion vector, and then a linear convergence significantly diagram, with locally adaptive thresholding instead of "Winner-Takes-All" neural network (Winner-Take-All, WTA), through the similarity of pixel gray scale and significant regional centroid of the adjacency to split the objectives and background, finally be interested in infrared image targets (including thermal targets and moving targets). Simulation results show that the method for the fusion system, the lower the contrast of the image after the video sequence scene moving target detection with good results.
Keywords :
feature extraction; image fusion; image motion analysis; image segmentation; infrared imaging; neural nets; object detection; video signal processing; brightness contrast; fusion system; image sequences; locally adaptive thresholding; motion vector; still images; video sequence; visual attention infrared target detection algorithm; visual feature extraction; winner-takes-all neural network; Brightness; Convergence; Feature extraction; Image sequences; Infrared detectors; Infrared imaging; Neural networks; Object detection; Pixel; Vectors; image fusion; infrared target detection; segmentation of threshold; visual attention model;
Conference_Titel :
Communications and Mobile Computing (CMC), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-6327-5
Electronic_ISBN :
978-1-4244-6328-2
DOI :
10.1109/CMC.2010.16
