Perspective image modeling for segmentation

This paper proposes a novel thresholding method for real time perspective image segmentation based on an image gray level probability distribution model. A perspective image can be modeled as a mixture of the background and the object in the image, which are farther modeled as two independent Gaussian distributions. Therefore, given an input perspective image, our method firstly derives the gray level distributions of the background and the object, respectively, based on the image histogram analysis. Then the optimum threshold can be obtained from the intersection of the derived distributions of the background and the object. Experimental results on currency watermark image segmentation for real time printing quality inspection are rather encouraging.