Method and system for optimizing print-scan simulations
View Patent ↗Systems and methods for utilizing a known histogram of a particular category of images to constrain a probabilistic print-scan model in order to provide a more accurate print-scan model are described. A probability function is defined that given a two-dimensional grayscale bitmap input image provides the probability that a particular pixel of the input image will have a particular gray level in the output image after print-scan processing. Additionally, an expected target histogram is input into the system and used to constrain or modify the probabilistic print-scan model for the input image to produce a deterministic print-scan model.
1. A computer implemented method for simulating an output image using an input image, a print-scan model with histogram constraints comprising:
obtaining a probabilistic print-scan model for simulating the output image;
obtaining an expected histogram of the input image; and
iteratively applying a histogram constraint to the probabilistic model using the computer to obtain a histogram constrained print-scan model;
performing a print-scan simulation using the computer by using the input image and the histogram constrained print-scan model to predict the output image,
wherein the input image is a copy detection pattern,
wherein the input image includes k pixels in a vector format assigned a gray level from a range of gray levels; and
the probabilistic print-scan model includes a 3-D histogram of probabilities with indexes for the k pixels and the range of gray levels.
2. The method according to claim 1 , wherein the input image is a gray scale image.
3. The method according to claim 1 , wherein the expected histogram comprises a 2-D histogram of expected gray values of the input image.
4. The method according to claim 3 , wherein the histogram constraint comprises:
(a) selecting the highest probability fro the 3-D histogram;
(b) determining if the 2-D histogram limit for the corresponding gray level has been exceeded;
(c) if the 2-D histogram limit for the corresponding gray level has been exceeded, removing the 3-D histogram column associated with that gray level;
(d) assigning the corresponding gray level to the corresponding pixel in the output image;
(e) removing the associated pixel row from the 3-D histogram; and
(f) repeating (a)-(e) until the output image is filled.
5. The method according to claim 1 , wherein the expected histogram is determined by scanning and processing a sample image in the same category as the input image.
6. The method according to claim 1 , wherein the expected histogram is obtained from a third party.
7. A computer implemented method for simulating an output image expected for a printer and an output media using an input image and a print-scan model with histogram constraints comprising:
obtaining a probabilistic print-scan model for simulating the output image, wherein the probabilistic print-scan model is associated with a printer type associated with the printer and a media type associated with the output media;
obtaining an expected histogram of the input image, wherein the expected histogram is associated with a category of images having similar histograms, the particular category being associated with the input image;
iteratively applying a histogram constraint to the probabilistic model using the computer to obtain a histogram constrained print-scan model for the printer, the output media and the category of images; and
performing a print-scan simulation using the computer with the input image and the histogram constrained print-scan model to produce a predicted the output image,
wherein the input image is a copy detection pattern,
wherein the input image includes k pixels in a vector format assigned a gray level from a range of gray levels; and
the probabilistic print-scan model includes a 3-D histogram of probabilities with indexes for the k pixels and the range of gray levels.
8. The method according to claim 7 , further comprising;
displaying the predicted output image.
9. The method according to claim 7 , further comprising;
printing the predicted output image.
10. The method according to claim 7 , wherein the expected histogram comprises a 2-D histogram of expected gray values of the input image.
11. The method according to claim 7 , wherein the histogram constraint comprises:
(a) selecting the highest probability fro the 3-D histogram;
(b) determining if the 2-D histogram limit for the corresponding gray level has been exceeded;
(c) if the 2-D histogram limit for the corresponding gray level has been exceeded, removing the 3-D histogram column associated with that gray level;
(d) assigning the corresponding gray level to the corresponding pixel in the output image;
(e) removing the associated pixel row from the 3-D histogram; and
(f) repeating (a)-(e) until the output image is filled.