INFRARED IMAGE MULTI-THRESHOLD SEGMENTATION ALGORITHM BASED ON IMPROVED PULSE COUPLED NEURAL NETWORKS
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TN976 TN911.73

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    Abstract:

    By considering the features of targets in infrared images, a new image segmentation algorithm based on the pulse coupled neural network (PCNN) and histogram method was presented. The proposed algorithm entirely abandons the mechanism of the time exponential decaying function and uses the results of the gray level histogram analysis as the interior thresholds of PCNN. Meanwhile,it reserves the advantage of bridging small spatial gaps and minor intensity variations.Experiment results demonstrate that the proposed algorithm can get more complete region and edge information of infrared images. It is also of much lower complexity and of higher speed than the original one.

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KONG Xiang Wei HUANG Jing SHI Hao. INFRARED IMAGE MULTI-THRESHOLD SEGMENTATION ALGORITHM BASED ON IMPROVED PULSE COUPLED NEURAL NETWORKS[J]. Journal of Infrared and Millimeter Waves,2001,20(5):365~369

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  • Received:
  • Revised:January 16,2001
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