Segmentation of infrared image using adaptive thresholding

A novel adaptive method of automatic threshold selection is proposed for image segmentation in this paper. An optimal threshold is selected by the discriminant criterion acquired from the gray-level statistic of the resultant target and background region. The theoretical analysis shows that correct image segmentation can be obtained for a low-contrast image with complex background using this method, no matter the proportion of the target is small or big. Moreover, the computing quantity and the processing time can be decreased greatly by setting the gray level selection region. Several experimental results are also presented to support the validity ofthis method.