Method and system for automatic detection and display of aspect ratio
View Patent ↗Certain embodiments of the invention may be found in a method and system for automatic aspect ratio detection and may comprise scanning lines in at least a selected portion of an image and locating a first reference pixel in one of the scanned lines. A corresponding sliding sum and a sliding number may be generated starting from the first reference pixel and a white edge determined based on the generated sliding sum and/or the generated sliding number. The first reference pixel may be a non-black pixel and a value which corresponds to and defines non-black may be variably defined. The sliding sum and the sliding number may utilize m bins, where m is greater than one (1). A luma sum threshold may be compared with the generated sliding sum to locate the white edge for aspect ratio detection.
1. A method for automatic aspect ratio detection, the method comprising:
scanning lines in at least a selected portion of an image;
locating a first reference pixel in one of said scanned lines;
generating a sliding sum of pixel values, starting from said first reference pixel;
generating a sliding number starting from said first reference pixel, said sliding number indicative of a number of non-black pixels in said scanned lines and said sliding number based on said sliding sum; and
determining a white edge based on one or both of said generated sliding sum and said generated sliding number.
2. The method according to claim 1 , wherein said first reference pixel is a non-black pixel based on an associated pixel value.
3. The method according to claim 2 , comprising defining a value that represents non-black for said non-black pixel.
4. The method according to claim 1 , comprising utilizing m bins for each of said sliding sum and said sliding number, where m is greater than one (1).
5. The method according to claim 1 , comprising comparing a luma sum threshold with said generated sliding sum to locate said white edge.
6. A machine-readable storage having stored thereon, a computer program having at least one code section for automatic aspect ratio detection, said at least one code section being executable by a machine for causing the machine to perform steps comprising:
scanning lines in at least a selected portion of an image;
locating a first reference pixel in one of said scanned lines;
generating a sliding sum of pixel values, starting from said first reference pixel;
generating a sliding number starting from said first reference pixel, said sliding number indicative of a number of non-black pixels in said scanned lines and said sliding number based on said sliding sum; and
determining a white edge based on one or both of said generated sliding sum and said generated sliding number.
7. The machine-readable storage according to claim 6 , wherein said first reference pixel is a non-black pixel based on an associated pixel value.
8. The machine-readable storage according to claim 7 , comprising code for defining a value that represents non-black for said non-black pixel.
9. The machine-readable storage according to claim 6 , comprising code for utilizing m bins for each of said sliding sum and said sliding number, where m is greater than one (1).
10. The machine-readable storage according to claim 6 , comprising code for comparing a luma sum threshold with said generated sliding sum to locate said white edge.
11. A system for automatic aspect ratio detection, the system comprising:
at least one processor for scanning lines in at least a selected portion of an image;
said at least one processor locates a first reference pixel in one of said scanned lines;
said at least one processor generates a sliding sum of pixel values, starting from said first reference pixel;
said at least one processor generates a sliding number starting from said first reference pixel, said sliding number indicative of a number of non-black pixels in said scanned lines and said sliding number based on said sliding sum; and
said at least one processor determines a white edge based on one or both of said generated sliding sum and said generated sliding number.
12. The system according to claim 11 , wherein said first reference pixel is a non-black pixel based on an associated pixel value.
13. The system according to claim 12 , wherein said at least one processor defines a value that represents non-black for said non-black pixel.
14. The system according to claim 11 , comprising utilizing m bins for each of said sliding sum and said sliding number, where m is greater than one (1).
15. The system according to claim 11 , wherein said at least one processor compares a luma sum threshold with said generated sliding sum to locate said white edge.
16. The system according to claim 11 , wherein said at least one processor is a host CPU or an on-chip processor.
17. A method for automatic aspect ratio detection, the method comprising:
scanning lines in at least a selected portion of an image;
locating a first reference pixel in one of said scanned lines;
generating a sliding sum of pixel values, starting from said first reference pixel;
generating a sliding number starting from said first reference pixel, said sliding number indicative of a number of non-black pixels in said scanned lines and said sliding number based on said sliding sum;
determining a white edge based on one or both of said generated sliding sum and said generated sliding number; and
utilizing m bins for each of said sliding sum and said sliding number, where m is greater than one (1).
18. The method according to claim 17 , comprising determining said sliding sum by calculating, sliding sum value[k]=prior sliding sum value[k]+(pixel value−non-black threshold), where k=(current column−left edge), prior sliding sum value[k] is initially zero (0) for each of said m bins, left edge is the column where the leftmost pixel is located, and k is not less than zero (0).
19. The method according to claim 18 , comprising, if k is not less than zero (0), incrementing sliding number[k] for each of said m bins to determine said sliding number.
20. The method according to claim 18 , comprising:
if k is less than zero (0):
sliding mod[k] rightmost values of said sliding sum out;
discarding said mod[k] rightmost values of said sliding sum; and
sliding in mod[k] zeroes (0s) in leftmost values of said sliding sum.
21. The method according to claim 18 , comprising:
if k is less than zero (0):
sliding mod[k] rightmost values of said sliding number out;
discarding said mod[k] rightmost values of said sliding number; and
sliding in mod[k] zeroes in leftmost values of said sliding number.
22. The method according to claim 21 , comprising:
if K is less than zero (0):
setting a left edge equivalent to said current column;
initializing k to zero (0); and
computing said sliding sum value [k].
23. A machine-readable storage having stored thereon, a computer program having at least one code section for automatic aspect ratio detection, said at least one code section being executable by a machine for causing the machine to perform steps comprising:
scanning lines in at least a selected portion of an image;
locating a first reference pixel in one of said scanned lines;
generating a sliding sum of pixel values, starting from said first reference pixel;
generating a sliding number starting from said first reference pixel, said sliding number indicative of a number of non-black pixels in said scanned lines and said sliding number based on said sliding sum;
determining a white edge based on one or both of said generated sliding sum and said generated sliding number; and
utilizing m bins for each of said sliding sum and said sliding number, where m is greater than one (1).
24. The machine-readable storage according to claim 23 , comprising code for determining said sliding sum by calculating, sliding sum value[k]=prior sliding sum value[k]+(pixel value−non-black threshold), where k=(current column−left edge), prior sliding sum value[k] is initially zero (0) for each of said m bins, left edge is the column where the leftmost pixel is located, and k is not less than zero (0).
25. The machine-readable storage according to claim 24 , comprising code for incrementing sliding number[k] for each of said m bins to determine said sliding number, if k is not less than zero (0).
26. The machine-readable storage according to claim 24 , comprising code for:
if k is less than zero (0):
sliding mod[k] rightmost values of said sliding sum out;
discarding said mod[k] rightmost values of said sliding sum; and
sliding in mod[k] zeroes (0s) in leftmost values of said sliding sum.
27. The machine-readable storage according to claim 24 , comprising code for:
if k is less than zero (0):
sliding mod[k] rightmost values of said sliding number out;
discarding said mod[k] rightmost values of said sliding number; and
sliding in mod[k] zeroes (0s) in leftmost values of said sliding number.
28. The machine-readable storage according to claim 27 , comprising code for:
if K is less than zero (0):
setting a left edge equivalent to said current column;
initializing k to zero (0); and
computing said sliding sum value [k].
29. A system for automatic aspect ratio detection, the system comprising:
at least one processor for scanning lines in at least a selected portion of an image;
said at least one processor locates a first reference pixel in one of said scanned lines;
said at least one processor generates a sliding sum of pixel values, starting from said first reference pixel;
said at least one processor generates a sliding number starting from said first reference pixel, said sliding number indicative of a number of non-black pixels in said scanned lines and said sliding number based on said sliding sum; and
said at least one processor determines a white edge based on one or both of said generated sliding sum and said generated sliding number.
30. The system according to claim 29 , comprising utilizing m bins for each of said sliding sum and said sliding number, where m is greater than one (1).
31. The system according to claim 30 , wherein said at least one processor determines said sliding sum by calculating, sliding sum value[k]=prior sliding sum value[k]+(pixel value−non-black threshold), where k=(current column−left edge), prior sliding sum value[k] is initially zero (0) for each of said m bins, left edge is the column where the leftmost pixel is located, and k is not less than zero (0).
32. The system according to claim 31 , wherein said at least one processor, if k is not less than zero (0), increments sliding number[k] for each of said m bins to determine said sliding number.
33. The system according to claim 31 , wherein said at least one processor:
if k is less than zero (0):
slides mod[k] rightmost values of said sliding sum out;
discards said mod[k] rightmost values of said sliding sum; and
slides in mod[k] zeroes (0s) in leftmost values of said sliding sum.
34. The system according to claim 31 , comprising:
if k is less than zero (0):
slides mod[k] rightmost values of said sliding number out;
discards said mod[k] rightmost values of said sliding number; and
slides in mod[k] zeroes (0s) in leftmost values of said sliding number.
35. The system according to claim 34 , wherein said at least one processor:
if K is less than zero (0):
sets a left edge equivalent to said current column;
initializes k to zero (0); and
computes said sliding sum value [k].