Intelligent multi-spectral IR image segmentation

Abstract

We present a neural network based multi-­‐spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. The neural net based segmentation method is compared with Wavelet-­‐threshold and Grab-­‐Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-­‐spectral IR images.