Image fragmentation for distortion correction of color space encoded image
Embodiments of the present disclosure can include devices for storing and exchanging color space encoded images. The encoded images can store input data into high capacity multi-colored composite two-dimensional pictures having different symbols organized in specific order using sets in a color space. The encoding can include performing two-level error correction and generating frames based on the color space for formatting and calibrating the encoded images during decoding. The decoding can use the frames to perform color restoration and distortion correction. The decoding can be based on a pseudo-Euclidean distance between a distorted color and a color in a color calibration cells. In some embodiments, an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
1. A computer-implemented method of encoding data using a color space, the method comprising:
receiving, at a capturing device, data for encoding;
determining, at the capturing device, a code sequence by performing error correction on the data;
creating, at the capturing device, colored cells to provide an encoded representation of the received data in an image by determining a color encoding for one or more codes in the code sequence by mapping the code sequence to a stream of integers, each integer in the stream of integers corresponding to a color in the color space for a cell in the image;
partitioning, at the capturing device, the colored cells into subimages of the image, the subimages providing smaller areas for assisting in decoding the image; and
creating, at the capturing device, one or more additional cells, including color calibration cells, adjoining the image, the one or more additional cells for assisting in decoding the image by determining a pseudo-Euclidean metric in the color space, the metric measuring distance including a measure of an average of: (a) a red component in the colored cells and (b) a red component in the color calibration cells.
2. The method of claim 1 , the one or more additional cells including a frame surrounding the image.
3. The method of claim 1 , wherein the pseudo-Euclidean metric is defined as:
Δ
C
=
(
X
+
r
_
256
)
Δ
R
2
+
Y
Δ
G
2
+
(
Z
+
255
-
r
_
256
)
Δ
B
2
wherein:
Δ C is a pseudo-Euclidean distance between two colors,
C 1 includes a red component R 1 , a green component G 1 , and a blue component B 1 ,
C 2 includes a red component R 2 , a green component G 2 , and a blue component B 2 ,
X, Y and Z represent coefficients,
ΔR=R 2 −R 1 ,
ΔG=G 2 −G 1 ,
ΔB=B 2 −B 1 , and
r
_
=
R
1
+
R
2
2
.
4. The method of claim 3 , wherein the coefficients of the pseudo-Euclidean metric are defined as X=2, Y=4 and Z=2.
5. A computer-implemented method of decoding an image using a color space, the method comprising:
receiving, at a processing device including a decoding module, an image to decode;
locating, at the decoding module, the image by locating one or more additional cells, including color calibration cells, adjoining the image;
locating, at the decoding module, one or more subimages of the image; and
for each subimage,
decoding, at the decoding module, data based at least in part on colored cells in the subimage and the one or more additional cells adjoining the image by determining a pseudo-Euclidean metric in the color space, the metric measuring distance including a measure of an average of: (a) a red component in the colored cells and (b) a red component in the color calibration cells.
6. The method of claim 5 , the one or more additional cells including a frame surrounding the image.
7. The method of claim 5 , wherein the pseudo-Euclidean metric is defined as:
Δ
C
=
(
X
+
r
_
256
)
Δ
R
2
+
Y
Δ
G
2
+
(
Z
+
255
-
r
_
256
)
Δ
B
2
wherein:
Δ C is a pseudo-Euclidean distance between two colors,
C 1 includes a red component R 1 , a green component G 1 , and a blue component B 1 ,
C 2 includes a red component R 2 , a green component G 2 , and a blue component B 2 ,
X, Y and Z represent coefficients,
ΔR=R 2 −R 1 ,
ΔG=G 2 −G 1 ,
ΔB=B 2 −B 1 , and
r
_
=
R
1
+
R
2
2
.
8. The method of claim 7 , wherein the coefficients of the pseudo-Euclidean metric are defined as X=2, Y=4 and Z=2.
9. A system for encoding data using a color space, the system comprising:
memory;
storage; and
at least one processor configured to use the memory and storage to:
receive data for encoding;
determine a code sequence by performing error correction on the data;
create colored cells to provide an encoded representation of the received data in an image by determining a color encoding for one or more codes in the code sequence by mapping the code sequence to a stream of integers, each integer in the stream of integers corresponding to a color in the color space for a cell in the image;
partition the colored cells into subimages of the image, the subimages providing smaller areas for assisting in decoding the image; and
create one or more additional cells, including color calibration cells, adjoining the image, the one or more additional cells for assisting in decoding the image by determining a pseudo-Euclidean metric in the color space, the metric measuring distance including a measure of an average of: (a) a red component in the colored cells and (b) a red component in the color calibration cells.
10. The system of claim 9 , the one or more additional cells including a frame surrounding the image.
11. The system of claim 9 , wherein the pseudo-Euclidean metric is defined as:
Δ
C
=
(
X
+
r
_
256
)
Δ
R
2
+
Y
Δ
G
2
+
(
Z
+
255
-
r
_
256
)
Δ
B
2
wherein:
Δ C is a pseudo-Euclidean distance between two colors,
C 1 includes a red component R 1 , a green component G 1 , and a blue component B 1 ,
C 2 includes a red component R 2 , a green component G 2 , and a blue component B 2 ,
X, Y and Z represent coefficients,
ΔR=R 2 −R 1 ,
ΔG=G 2 −G 1 ,
ΔB=B 2 −B 1 , and
r
_
=
R
1
+
R
2
2
.
12. The system of claim 11 , wherein the coefficients of the pseudo-Euclidean metric are defined as X=2, Y=4 and Z=2.
13. A system for decoding an image using a color space, the system comprising:
memory;
storage; and
at least one processor configured to:
receive an image to decode;
locate the image by locating one or more additional cells, including color calibration cells, adjoining the image;
locate one or more subimages of the image; and
for each subimage,
decode data based at least in part on colored cells in the subimage and the one or more additional cells adjoining the image by determining a pseudo-Euclidean metric in the color space, the metric measuring distance including a measure of an average of: (a) a red component in the colored cells and (b) a red component in the color calibration cells.
14. The system of claim 13 , the one or more additional cells including a frame surrounding the image.
15. The system of claim 13 , wherein the pseudo-Euclidean metric is defined as:
Δ
C
=
(
X
+
r
_
256
)
Δ
R
2
+
Y
Δ
G
2
+
(
Z
+
255
-
r
_
256
)
Δ
B
2
wherein:
Δ C is a pseudo-Euclidean distance between two colors,
C 1 includes a red component R 1 , a green component G 1 , and a blue component B 1 ,
C 2 includes a red component R 2 , a green component G 2 , and a blue component B 2 ,
X, Y and Z represent coefficients,
ΔR=R 2 −R 1 ,
ΔG=G 2 −G 1 ,
ΔB=B 2 −B 1 , and
r
_
=
R
1
+
R
2
2
.
16. The system of claim 15 , wherein the coefficients of the pseudo-Euclidean metric are defined as X=2, Y=4 and Z=2.