A level set based inpainting approach for fragmentary human bodies in binarized infrared images
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Abstract:
A number of image segmentation algorithms frequently fragmentize human targets in infrared images, therefore, an inpainting procedure is always needed for further application. The inpainting is transformed to be a segmentation process. Firstly, Schrdinger transform connects fragmentized human parts. Then a level set model integrating image region and boundary information is proposed to extract the connected regions produced by the Schrdinger transform, and finally the inpainting is done when the model converged to complete the segmentation. Experiments show the proposed algorithm recognizes and locates human parts automatically, fills gaps correctly, connects broken human silhouettes smoothly. The objective indictor of shape similarity between inpainting results and relevant ground-truths is above 80%, as well as the internal fragmentary proportion below 4%. With optimized parameters the approach is robust to noise disturbance.