Systems and methods for pattern stitching and decoding using multiple captured images
Systems and methods read machine readable symbols, the systems and methods capture multiple images of the symbol and can locate symbol data region(s) from an image even when the symbol data is corrupted and not decodable. Binary matrices are generated of the symbol data regions obtained from the multiple images and can be accumulated to generate a decodable image. A correspondence can be established among multiple images acquired on the same symbol when the symbol has moved from one image to the next.
1. A system for decoding a symbol using images of the symbol, the system comprising:
an imaging device, the imaging device to acquire a first image and a second image, the first image including a first symbol data region, and the second image including a second symbol data region; and
a processor, the processor operatively coupled to the imaging device, the processor to execute a data stitching algorithm, wherein the data stitching algorithm generates a synthetic model of the symbol, the synthetic model being a model of a plurality of known features of a particular symbol, the data stitching algorithm correlates the synthetic model of the symbol with at least one of the first image and the second image, the data stitching algorithm further converts the first symbol data region into a first binary matrix and the second symbol data region into a second binary matrix, the data stitching algorithm accumulating the first binary matrix with the second binary matrix to generate an accumulative binary matrix, the accumulative binary matrix being a decodable representation of the symbol.
2. The system according to claim 1 ,
wherein the first image is acquired using a first set of acquisition parameters, and the second image is acquired using a second set of acquisition parameters, the second set of acquisition parameters being different than the first set of acquisition parameters.
3. The system according to claim 1 ,
wherein the first symbol data region and the second symbol data region overlap.
4. The system according to claim 1 ,
wherein a portion of at least one of the first symbol data region and the second symbol data region is corrupt and not decodable.
5. The system according to claim 1 ,
wherein the accumulated binary matrix includes at least one pattern recognition feature.
6. The system according to claim 1 ,
wherein the first symbol data region has a first position and a first scale, and the second symbol data region has a second position and a second scale, the second position and the second scale being different than the first position and the second scale; and
the data stitching algorithm further generating a correspondence, the correspondence to associate the first position and the first scale and the second position and the second scale.
7. The system according to claim 1 ,
wherein the first image includes a first polarity and the second image includes a second polarity different from the first polarity.
8. A system for establishing a correspondence between a first image and a subsequent image of a machine readable symbol, the system comprising:
an imaging device, the imaging device to acquire the first image and the subsequent image, the first image including a first symbol data region, and the subsequent image including a subsequent symbol data region, the first symbol data region having a first position and a first scale, and the subsequent symbol data region having a second position and a second scale, the second position and the second scale being different than the first position and the first scale;
a processor, the processor operatively coupled to the imaging device, the processor to execute a data stitching algorithm, wherein the data stitching algorithm generates a synthetic model of the machine readable symbol, the synthetic model being a model of a plurality of known features of a particular symbol, and performs a correlation on a synthetic model position to the second position and the second scale of the subsequent symbol data region; and
based on the correlation, the second position and the second scale of the subsequent symbol data region is adjusted to produce a refined subsequent image, such that the first image and the subsequent image can be stitched together for decoding.
9. The system according to claim 8 ,
wherein the data stitching algorithm converts the first symbol data region from the first image into a first binary matrix and the subsequent symbol data region from the refined subsequent image into a second binary matrix, the data stitching algorithm accumulating the first binary matrix with the second binary matrix to generate an accumulative binary matrix, the accumulative binary matrix being a decodable representation of the symbol.
10. The system according to claim 8 ,
wherein establishing the correspondence further includes maximizing a correlation score in a parameter space.
11. The system according to claim 10 ,
wherein the correlation uses an image analysis method, the correlation to produce a set of features to establish the correlation score.
12. The system according to claim 8 ,
wherein the imaging device is a handheld imaging device.
13. The system according to claim 8 ,
wherein the machine readable symbol is an alphanumeric symbol.
14. The system according to claim 8 ,
wherein the machine readable symbol is a 2D matrix symbol.
15. A method for decoding a symbol using images of the symbol, the method comprising:
generating a synthetic model of the symbol, the synthetic model being a model of a plurality of known features of a particular symbol;
acquiring a first image and a second image using an imaging device, the first image including a first symbol data region, and the second image including a second symbol data region;
correlating the synthetic model of the symbol with the first image and extracting a first binary matrix
correlating the synthetic model of the symbol with the second image and extracting a second binary matrix;
accumulating the first binary matrix with the second binary matrix; and
generating an accumulative binary matrix, the accumulative binary matrix being a decodable representation of the symbol.
16. The method according to claim 15 ,
further including executing a data stitching algorithm using a processor operatively coupled to the imaging device, the data stitching algorithm performing the accumulating and the generating steps.
17. The method according to claim 15 ,
further including decoding the accumulative binary matrix using symbol decoding software.