Creating hash values indicative of differences in images
A computer implemented method for hashing an image is provided that includes: receiving a reference image frame; deriving an array of reference hash values to represent the reference image frame, wherein the array of reference hash values includes a first reference hash value, a second reference hash value, and a third reference hash value; receiving an test image frame; deriving an array of hash values to represent the test image frame, wherein the array of hash values includes a first test hash value, a second test hash value, and a third test hash value; subtracting the array of test hash values representing the test image frame from the array of reference hash values representing the reference image frame to produce a delta array, wherein the delta array is indicative of an area where the test image frame differs from the reference image frame.
1. A computer implemented method of hashing an image, comprising:
receiving a reference image frame;
deriving an array of reference hash values to represent the reference image frame, wherein the array of reference hash values includes a first reference hash value, a second reference hash value, and a third reference hash value;
receiving an test image frame;
deriving an array of hash values to represent the test image frame, wherein the array of hash values includes a first test hash value, a second test hash value, and a third test hash value; and
subtracting the array of test hash values representing the test image frame from the array of reference hash values representing the reference image frame to produce a delta array,
wherein the delta array is indicative of an area where the test image frame differs from the reference image frame,
wherein the first reference hash value is Hash(Y), the second reference hash value is Hash(U) and the third reference hash value is Hash(V), and the reference array is ref[Hash(Y), Hash(U), Hash(V)] and wherein the first test hash value is Hash(Y), the second test hash value is Hash(U) and the third test hash value is Hash(V), and the test array is test[Hash(Y), Hash(U), Hash(V)], and wherein the delta array is delta[Hash(Y), Hash(U), Hash(V)], and
wherein Hash(Y) is determined according to a hash function:
Hash(Y)=Σ(w ij *(Y value of a pixel at coordinates (i,j))
wherein w ij is a value represented by (i+j).
2. The method of claim 1 , further comprising:
storing the array of reference hash values representing the reference image frame.
3. The method of claim 1 , wherein each hash value corresponds to an individual component value.
4. The method of claim 3 , wherein the individual component value is selected from a YUV domain or a RGB domain.
5. The method of claim 4 , wherein the YUV domain or RGB domain is represented by 8-bit values for each component.
6. The method of claim 4 , wherein the YUV domain or RGB domain is represented by 4-bit values for each component.
7. The method of claim 1 , wherein errors in the image frame occur in two or more domains and wherein the hash values provide the domains.
8. The method of claim 1 , wherein the delta array is indicative of the position of errors in the image frame.
9. The method of claim 1 , wherein the first reference hash value Hash(Y), the second reference hash value Hash(U) and the third reference hash value Hash(V) as well as the first test hash value Hash(Y), the second test hash value is Hash(U) and the third test hash value Hash(V) are determined using logarithm or multiplier hash functions.
10. The method of claim 1 , wherein if the test image frame differs from the reference image frame, the delta array includes non-negative numbers for each of Hash (Y), Hash(U), and Hash(V).
11. The method of claim 1 , wherein if the test image frame is similar to the reference image frame, the delta array includes the value 0 for each of Hash (Y), Hash(U), and Hash(V).
12. The method of claim 1 , further comprising:
graphing delta[Hash(Y)] on an X-Y plane using a probability picture determined by hash function w ij .
13. A computer implemented method of hashing an image, comprising:
receiving a reference image frame;
deriving an array of reference hash values to represent the reference image frame, wherein the array of reference hash values includes a first reference hash value, a second reference hash value, and a third reference hash value;
receiving an test image frame;
deriving an array of hash values to represent the test image frame, wherein the array of hash values includes a first test hash value, a second test hash value, and a third test hash value; and
subtracting the array of test hash values representing the test image frame from the array of reference hash values representing the reference image frame to produce a delta array,
wherein the delta array is indicative of an area where the test image frame differs from the reference image frame,
wherein the first reference hash value is Hash(Y), the second reference hash value is Hash(U) and the third reference hash value is Hash(V), and the reference array is ref[Hash(Y), Hash(U), Hash(V)] and wherein the first test hash value is Hash(Y), the second test hash value is Hash(U) and the third test hash value is Hash(V), and the test array is test[Hash(Y), Hash(U), Hash(V)], and wherein the delta array is delta[Hash(Y), Hash(U), Hash(V)], and
wherein Hash(U) is determined according to a hash function:
Hash(U)=Σ(t ij *(U value of a pixel at coordinates (i,j))
wherein t ij is a value represented by (length−i)+(height−j).
14. The method of claim 13 , further comprising:
graphing delta[Hash(U)] on an X-Y plane using a probability picture determined by hash function t ij .
15. A computer implemented method of hashing an image, comprising:
receiving a reference image frame;
deriving an array of reference hash values to represent the reference image frame, wherein the array of reference hash values includes a first reference hash value, a second reference hash value, and a third reference hash value;
receiving an test image frame;
deriving an array of hash values to represent the test image frame, wherein the array of hash values includes a first test hash value, a second test hash value, and a third test hash value; and
subtracting the array of test hash values representing the test image frame from the array of reference hash values representing the reference image frame to produce a delta array,
wherein the delta array is indicative of an area where the test image frame differs from the reference image frame,
wherein the first reference hash value is Hash(Y), the second reference hash value is Hash(U) and the third reference hash value is Hash(V), and the reference array is ref[Hash(Y), Hash(U), Hash(V)] and wherein the first test hash value is Hash(Y), the second test hash value is Hash(U) and the third test hash value is Hash(V), and the test array is test[Hash(Y), Hash(U), Hash(V)], and wherein the delta array is delta[Hash(Y), Hash(U), Hash(V)], and
wherein Hash(V) is determined according to a hash function:
Hash(V)=Σ(s ij *(V value of a pixel at coordinates (i,j))
wherein s ij is a value represented by (i+j) when i≦length/2 and j≦height/2;
wherein s ij is a value represented by (i+height−j) when i≦length/2 and j>height/2;
wherein s ij is a value represented by (length−i+j) when i>length/2 and j≦height/2;
wherein s ij is a value represented by (length−i+height−j) when i>length/2 and j>height/2.
16. The method of claim 15 , further comprising:
graphing delta[Hash(V)] on an X-Y plane using a probability picture determined by hash function s ij .