Method, terminal and computer-readable recording medium for deblurring barcode image

1. A method for deblurring a barcode image inputted through a mobile terminal comprising the steps of:

(a) acquiring the mobile terminal's unique n OTFs (optical transfer functions), from 1-st to n-th OTFs, which are calculated by varying focal lengths for a subject;

(b) if a barcode image is inputted through the mobile terminal, (i) fixing a specific value among NSRs (noise-to-signal ratios) in an available scope as a value to be applied to an error metric of Wiener filtering, (ii) applying n PSFs (point spread functions) calculated from the n OTFs to the error metric of the Wiener filtering by a binary search algorithm and (iii) determining whether the result of the application to the error metric of the Wiener filtering is not exceeding the pre-set threshold or not; and

(c) selecting a PSF value and an NSR value as values of Wiener filtering if the result of the application to the error metric of the Wiener filtering is not exceeding the pre-set threshold and then performing the Wiener filtering to the inputted barcode image by using the selected PSF value and the selected NSR value.

2. The method of claim 1 wherein, at the step of (b), the specific value of NSR is extracted from the inputted barcode image and then the specific value is fixed as the value to be applied to the error metric of the Wiener filtering.

3. The method of claim 2 wherein the step of (b) includes the step of:

(b1) performing a process of, while the value of the NSR to be applied to the error metric is fixed, applying a first PSF corresponding to a point where a distance d is increased from a point of n/2 (wherein an initial value of d is set as n/2), a second PSF corresponding to a point where the distance d is decreased from the point of n/2, and a third PSF of the point corresponding to n/2 to the error metric of the Wiener filtering to get a minimum error value among error values of the above-mentioned three cases in the step (b1);

(b2) performing a process of, after setting d as d/2 if the minimum error value is bigger than the pre-set threshold, applying a fourth PSF of a point where d (now which is n/4) is increased from a point corresponding to the minimum error value, a fifth PSF of a point where d is decreased from the point corresponding to the minimum error value, and a sixth PSF of the point corresponding to the minimum error value to the error metric of the Wiener filtering to thereby get a newly determined minimum error value among error values of the above-mentioned three cases in the step (b2); and

(b3) iterating the step of (b2) while setting the minimum error value as the newly determined minimum value if the newly determined minimum error value is bigger than the pre-set threshold.

4. The method of claim 3 wherein, at the step of (b2), the iteration is performed until the newly determined minimum value becomes the threshold or less.

5. A terminal for deblurring a barcode image inputted therethrough comprising:

a PSF managing part for calculating n PSFs from n OTFs, i.e., 1-st to n-th OTFs, after the terminal's unique n OTFs which are calculated by varying focal lengths for a subject are acquired;

an error metric applying part for, if a barcode image is inputted therefrom, (i) fixing a specific value among NSRs (noise-to-signal ratios) in an available scope as a value to be applied to an error metric of Wiener filtering, (ii) applying n PSFs (point spread functions) calculated from the n OTFs to the error metric of the Wiener filtering by a binary search algorithm and (iii) determining whether the result of the application to the error metric of the Wiener filtering is not exceeding the pre-set threshold or not; and

a filtering performing part for selecting a PSF value and an NSR value as values of Wiener filtering if the result of the application to the error metric of the Wiener filtering is not exceeding the pre-set threshold and then performing the Wiener filtering to the inputted barcode image by using the selected PSF value and the selected NSR value.

6. The terminal of claim 5 wherein the error metric applying part extracts the specific value of NSR from the inputted barcode image and then fixes the specific value as the value to be applied to the error metric of the Wiener filtering.

7. The terminal of claim 6 wherein, while the application value of the NSR is fixed, the error metric applying part (i) performs a function of, while the value of the NSR to be applied to the error metric is fixed, applying a first PSF corresponding to a point where a distance d is increased from a point of n/2 (wherein an initial value of d is set as n/2), a second PSF corresponding to a point where the distance d is decreased from the point of n/2, and a third PSF of the point corresponding to n/2 to the error metric of the Wiener filtering to get a minimum error value among error values of the above-mentioned three cases in the function (i); (ii) performs a function of, after setting d as d/2 if the minimum error value is bigger than the pre-set threshold, applying a fourth PSF of a point where d (now which is n/4) is increased from a point corresponding to the minimum error value, a fifth PSF of a point where d is decreased from the point corresponding to the minimum error value, and a sixth PSF of the point corresponding to the minimum error value to the error metric of the Wiener filtering to thereby get a newly determined minimum error value among error values of the above-mentioned three cases in the function (ii); and (iii) iterates the function of (ii) while setting the minimum error value as the newly determined minimum value if the newly determined minimum error value is bigger than the pre-set threshold.

8. The terminal of claim 7 wherein the error metric applying part performs the iteration until the newly determined minimum value becomes the threshold value or less.

9. One or more non-transitory computer-readable recording media having stored thereon a computer program that, when executed by one or more processors, causes the one or more processors to perform acts including:

acquiring the mobile terminal's unique n OTFs (optical transfer functions), from 1-st to n-th OTFs, which are calculated by varying focal lengths for a subject;

if a barcode image is inputted through the mobile terminal, (i) fixing a specific value among NSRs (noise-to-signal ratios) in an available scope as a value to be applied to an error metric of Wiener filtering, (ii) applying n PSFs (point spread functions) calculated from the n OTFs to the error metric of the Wiener filtering by a binary search algorithm and (iii) determining whether the result of the application to the error metric of the Wiener filtering is not exceeding the pre-set threshold or not; and

selecting a PSF value and an NSR value as values of Wiener filtering if the result of the application to the error metric of the Wiener filtering is not exceeding the pre-set threshold and then performing the Wiener filtering to the inputted barcode image by using the selected PSF value and the selected NSR value.