WO2014140895A2 - Data storage and exchange device for color space encoded images - Google Patents
Data storage and exchange device for color space encoded images Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/46—Colour picture communication systems
- H04N1/64—Systems for the transmission or the storage of the colour picture signal; Details therefor, e.g. coding or decoding means therefor
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
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Definitions
- the present disclosure relates to a data storage and exchange device for color space encoded images, and methods of encoding and decoding color space encoded images. More particularly, the present disclosure relates to encoding and decoding of machine-based data using high capacity multi-colored composite two-dimensional pictures having different symbols organized in specific order and sets in a color space.
- Example data capture technologies include bar codes, QR codes, Radio Frequency Identification (RFID) and Near Field Communication (NFC). Most of these technologies are used as either a visible or an invisible tag to connect these databases and user devices.
- RFID Radio Frequency Identification
- NFC Near Field Communication
- Wi-Fi Wireless Fidelity
- End user devices such as smartphones and tablets are frequently equipped with photo and/or video cameras. These cameras can be used for capturing information presented in different visual forms.
- Bar codes have been used for mobile applications to deliver a multitude of different mobile services over mobile phones and other mobile communication or computing devices. Such applications range from providing Uniform Resource Locator (URL) information to link a mobile device to the Internet, through to using a bar code as a form of e- ticket for airlines or event admissions.
- URL Uniform Resource Locator
- Traditional approaches to higher capacity bar codes include: (i) using a colored symbol set and (ii) increasing the size of the bar code.
- the traditional data capacity of ID and 2D bar codes is severely limited. This severely limited data capacity constrains possible applications of ID and 2D bar codes, and their primary task is simply linking camera phones to designated Web sites. Additional tasks may then be performed based on the Web site. This operation again is based on using of Wi-Fi or 3G connectivity.
- bar codes can be used to provide 2D encoded data, they have not been used to provide real storage devices and media.
- 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 color calibration cells.
- an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
- devices and non-transitory computer program products are provided for data storage and exchange.
- Certain embodiments include a device for data storage and exchange, including an interface for receiving data and at least one processor configured to encode the data.
- the at least one processor is configured to encode the data by creating colored cells to provide an encoded representation of the received data in an image by processing the received data to obtain 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 and creating one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- Non-transitory computer program products for data storage and exchange.
- the non-transitory computer program product can be tangibly embodied in a computer-readable medium.
- the non-transitory computer program product can include instructions operable to cause a data processing apparatus to create colored cells to provide an encoded representation of the received data in an image by processing the received data to obtain a stream of integers. Each integer in the stream of integers can correspond to a color in the color space for a cell in the image.
- the instructions are also operable to cause a data processing apparatus to create one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- Certain embodiments include a device for data storage and exchange, including a camera and at least one processor configured to decode the data.
- the at least one processor is configured to decode the data by receiving, from the camera, an image having colored cells corresponding to a stream of integers encoding the data, locating the image by locating one or more additional cells adjoining the image, and decoding data based at least in part on the colored cells and the one or more additional cells adjoining the image.
- Non-transitory computer program products for data storage and exchange.
- the non-transitory computer program product can be tangibly embodied in a computer-readable medium.
- the non-transitory computer program product can include instructions operable to cause a data processing apparatus to receive, from a camera, an image having colored cells corresponding to a stream of integers encoding the data, locate the image by locating one or more additional cells adjoining the image, and decode data based at least in part on the colored cells and the one or more additional cells adjoining the image.
- the device can include a display to display the image.
- the device and non-transitory computer program products can also be configured to store the image in the storage after encoding the data.
- the device and non-transitory computer program products can also be configured to display the image on a display.
- the additional cells can include a frame surrounding the image.
- the additional cells can include color calibration cells adjoining the 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 color calibration cells.
- an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
- Certain embodiments include methods for encoding data using a color space.
- the method includes receiving data for encoding and creating colored cells within a color space to provide an encoded representation of the received data in an image by processing the received data to obtain a stream of integers. Each integer in the stream of integers corresponds to a color in the color space for a cell in the image.
- the method also includes creating one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- Certain embodiments include systems for encoding data using a color space.
- the system includes at least one processor configured to receive data for encoding, create colored cells within a color space to provide an encoded representation of the received data in an image by processing the received data to obtain 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, and create one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- the creating the colored cells can include determining a code sequence by performing error correction on the data and determining the colors.
- the steps of determining the colors are processing one or more codes in the code sequence to obtain the stream of integers and mapping the resulting integers to a color in one or more color calibration cells, the one or more color calibration cells containing one or more samples of colors used in the encoded image.
- the creating the colored cells can include scrambling the received data and determining the colors by processing the scrambled data to obtain the stream of integers and mapping the resulting integers to a color in one or more color calibration cells, the one or more color calibration cells containing one or more samples of colors used in the encoded image.
- the creating the colored cells can include determining a code sequence by performing error correction on the data, scrambling the code sequence, and determining the colors.
- the steps of determining the colors are processing one or more codes in the scrambled code sequence to obtain the stream of integers and mapping the resulting integers to a color in one or more color calibration cells, the one or more color calibration cells containing one or more samples of colors used in the encoded image.
- the one or more additional cells can include a frame surrounding the image.
- the one or more additional cells can include color calibration cells adjoining the image.
- Certain embodiments include methods for decoding an image using a color space.
- the method includes receiving an image having colored cells corresponding to a stream of integers encoding data, locating the image by locating one or more additional cells adjoining the image, and decoding data based at least in part on the colored cells and the one or more additional cells adjoining the image.
- Certain embodiments include systems for decoding an image using a color space.
- the system includes at least one processor configured to receive an image having colored cells corresponding to a stream of integers encoding data, locate the image by locating one or more additional cells adjoining the image, and decode data based at least in part on the colored cells and the one or more additional cells adjoining the image.
- the decoding data can include determining a pseudo-Euclidean metric in a color space.
- the metric measures distance between a colored cell in the image and a sample color in one or more color calibration cells of the image.
- the one or more additional cells can include a frame surrounding the image.
- the one or more additional cells can include color calibration cells adjoining the 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 color calibration cells.
- an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
- Certain embodiments include methods for decoding an image using a color space.
- the method includes receiving an image having colored cells corresponding to a stream of integers encoding data and comparing a colored cell to one or more sample colors in one or more color calibration cells of the image.
- the method also includes determining an original color of the colored cell to be a sample color in the one or more color calibration cells by determining a pseudo-Euclidean metric in the color space.
- the metric measures distance between a detected color for the color cell and the one or more sample colors in the one or more color calibration cells.
- the method also includes decoding the colored cell based at least in part on the determined original color of the colored cell.
- Certain embodiments include systems for decoding an image using a color space, including at least one processor.
- the at least one processor is configured to receive an image having colored cells corresponding to a stream of integers encoding data, compare a colored cell to one or more sample colors in one or more color calibration cells of the image, and determine an original color of the colored cell to be a sample color in the one or more color calibration cells by determining a pseudo-Euclidean metric in the color space.
- the metric measures distance between a detected color for the color cell and the one or more sample colors in the one or more color calibration cells.
- the at least one processor is further configured to decode the colored cell based at least in part on the determined original color of the colored cell.
- Certain embodiments include non-transitory computer program products for decoding an image using a color space.
- the non-transitory computer program product is tangibly embodied in a computer-readable medium.
- the non-transitory computer program product includes instructions operable to cause a data processing apparatus to receive an image having colored cells corresponding to a stream of integers encoding data, compare a colored cell to one or more sample colors in one or more color calibration cells of the image, and determine an original color of the colored cell to be a sample color in the one or more color calibration cells by determining a pseudo-Euclidean metric in the color space.
- the metric measures distance between a detected color for the color cell and the one or more sample colors in the one or more color calibration cells.
- the instructions are further operable to cause a data processing apparatus to decode the colored cell based at least in part on the determined original color of the colored cell.
- the embodiments described herein can include additional aspects of the present invention.
- the one or more additional cells can include a frame surrounding the image.
- the one or more additional cells can include color calibration cells adjoining the image.
- Embodiments of the present disclosure can include devices, methods, and non- transitory computer program products 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 color calibration cells.
- an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
- Certain embodiments include methods for encoding data using a color space.
- the method includes receiving data for encoding, dividing the data into a bit array, and appending first source control data to one or more groups of bits in the bit array based at least in part on performing error correction on the group of bits.
- the method also includes dividing the one or more groups of bits in the bit array into half-groups, appending second source control data to the half-groups based at least in part on performing error correction on the one or more half-groups, and determining a code sequence based at least in part on the bits, half-groups, first source control data, and second source control data.
- the method also includes creating colored cells within a color space 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 and creating one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- Certain embodiments include methods for decoding an image using a color space.
- the method includes receiving an image having colored cells corresponding to a stream of integers encoding data, restoring at least one of correctable errors and unrepairable erasures in the image using error correction, and comparing a colored cell of the image to one or more sample colors in one or more color calibration cells of the image.
- the method also includes determining an original color of the colored cell to be a sample color in the one or more color calibration cells by determining a pseudo-Euclidean metric in the color space. The metric measures distance between a detected color for the color cell and the one or more sample colors in the one or more color calibration cells.
- the method also includes decoding the colored cell based at least in part on the determined original color of the colored cell.
- Certain embodiments include systems for encoding data using a color space.
- the system includes at least one processor.
- the at least one processor is configured to receive data for encoding, divide the data into a bit array, and append first source control data to one or more groups of bits in the bit array based at least in part on performing error correction on the group of bits.
- the at least one processor is also configured to divide the one or more groups of bits in the bit array into half-groups, append second source control data to the half- groups based at least in part on performing error correction on the one or more half-groups, and determine a code sequence based at least in part on the bits, half-groups, first source control data, and second source control data.
- the at least one processor is further configured to create colored cells within a color space 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 and create one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- Certain embodiments include systems for decoding an image using a color space.
- the system includes at least one processor.
- the at least one processor is configured to receive an image having colored cells corresponding to a stream of integers encoding data, restore at least one of correctable errors and unrepairable erasures in the image using error correction, and compare a colored cell of the image to one or more sample colors in one or more color calibration cells of the image.
- the at least one processor is also configured to determine an original color of the colored cell to be a sample color in the one or more color calibration cells by determining a pseudo-Euclidean metric in the color space. The metric measures distance between a detected color for the color cell and the one or more sample colors in the one or more color calibration cells.
- the at least one processor is further configured to decode the colored cell based at least in part on the determined original color of the colored cell.
- the embodiments described herein can include additional aspects of the present invention.
- the additional cells can include a frame surrounding the image.
- the additional cells can include color calibration cells adjoining the 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 color calibration cells.
- an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
- Certain embodiments include methods for correcting distortion in an image capture.
- the method includes locating one or more frames of an image having colored cells corresponding to a stream of integers encoding data and determining one or more curves, the one or more curves fitting frames in the one or more frames, the one or more curves defining an area of the image.
- the method also includes mapping the area of the image defined by the one or more curves onto a rectangle based at least in part on the one or more curves and correcting distortion in the image capture by straightening the image based at least in part on the mapping.
- Certain embodiments include systems for correcting distortion in an image capture.
- the system includes at least one processor configured to locate one or more frames of an image having colored cells corresponding to a stream of integers encoding data and determine one or more curves, the one or more curves fitting frames in the one or more frames, the one or more curves defining an area of the image.
- the at least one processor is also configured to map the area of the image defined by the one or more curves onto a rectangle based at least in part on the one or more curves and correct distortion in the image capture by straightening the image based at least in part on the mapping.
- Certain embodiments include non-transitory computer program products for correcting distortion in an image capture.
- the non-transitory computer program product is tangibly embodied in a computer-readable medium.
- the non-transitory computer program product includes instructions operable to cause a data processing apparatus to locate one or more frames of an image having colored cells corresponding to a stream of integers encoding data and determine one or more curves, the one or more curves fitting frames in the one or more frames.
- the one or more curves define an area of the image.
- the instructions are also operable to map the area of the image defined by the one or more curves onto a rectangle based at least in part on the one or more curves and correct distortion in the image capture by straightening the image based at least in part on the mapping.
- 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 color calibration cells.
- an encoded image can be further divided into sub-images during encoding for simplified distortion correction.
- Certain embodiments include methods of encoding data using a color space.
- the method includes receiving data for encoding and determining a code sequence by performing error correction on the data.
- the method also includes creating 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 corresponds to a color in the color space for a cell in the image.
- the method further includes partitioning the colored cells into subimages of the image, the subimages providing smaller areas for assisting in decoding the image and creating one or more additional cells adjoining the image, the one or more additional cells for assisting in decoding the image.
- Certain embodiments include methods of decoding an image using a color space.
- the method includes receiving an image to decode, locating the image by locating one or more additional cells adjoining the image, and locating one or more subimages of the image.
- the method also includes, for each subimage, decoding data based at least in part on colored cells in the subimage and the one or more additional cells adjoining the image.
- Certain embodiments include systems for encoding data using a color space.
- the system includes one or more displays and storage.
- the system also includes at least one processor configured to receive data for encoding, determine a code sequence by performing error correction on the data, and 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 corresponds to a color in the color space for a cell in the image.
- the at least one processor is further configured to 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 adjoining the image, the one or more additional cells for assisting in decoding the image.
- Certain embodiments include systems for decoding an image using a color space.
- the system includes one or more displays and storage.
- the system also includes at least one processor configured to receive an image to decode, locate the image by locating one or more additional cells adjoining the image, and locate one or more subimages of the image. For each subimage, the at least one processor is further configured to decode data based at least in part on colored cells in the subimage and the one or more additional cells adjoining the image.
- the additional cells can include a frame surrounding the image.
- the additional cells can include color calibration cells adjoining the image.
- FIG. 1 illustrates a system for storing, encoding, and decoding a 2D color space image in accordance with certain embodiments of the present disclosure.
- FIGS. 2A-2B illustrate the 2D color space encoded image in accordance with certain embodiments of the present disclosure.
- FIG. 3 illustrates a method that the system performs for encoding an image in accordance with certain embodiments of the present disclosure.
- FIG. 4 illustrates a method that the system performs for decoding an image in accordance with certain embodiments of the present disclosure.
- FIG. 5 illustrates a block diagram of color calibration cells for restoration of proper color based on distinguishable color samples in accordance with certain embodiments of the present disclosure.
- FIG. 6 illustrates a block diagram of a frame arrangement for geometrical distortion correction of an encoded image in accordance with certain embodiments of the present disclosure.
- FIG. 7 illustrates a block diagram for frame fragmentation for distortion correction in accordance with certain embodiments of the present disclosure.
- the present systems and methods allow for use of 2D color-space codes to encode images with greater data capacity.
- the 2D color-space encoded images described herein can provide a wide variety of applications, regardless of network connectivity.
- the present systems and methods allow a sufficient amount of data or even an entire database to be encoded and placed in a storage device using the 2D images encoded and organized by color- space codes as described herein.
- the present disclosure has utility in, for example, data back-up storage
- Figure 1 illustrates a system 100 for storing, encoding, and decoding a 2D color space image in accordance with certain embodiments of the present disclosure.
- System 100 includes a 2D color space image 102.
- System 100 can encode any type of desired machine- based data.
- Non-limiting examples of machine-based data include text 104a, books 104b (containing, for example, text and images), databases 104c, photographs 104d or other artwork, images, video, film, or movies, music 104e, or any other type of binary data 104f.
- capturing of desired data can be done using a conventional camera or scanner, or a smartphone or tablet camera.
- a user can encode selected information into a 2D color-space coded image and print the image on any desired media (e.g., paper, textile, plastic, etc.).
- the 2D color-space coded image can also be depicted on any display, including posters, TV screens or computer monitors, as well as displayed on mobile devices such as smartphones or tablets. Digital photo cameras can be used as display devices as well.
- the image code can be decoded and the encoded data can be read.
- the present systems and methods allow information to be retrieved, decoded, and saved in the memory of a device or presented on a display for further use.
- the decoded data can be read on a laptop computer 106a or a desktop computer 106b, a smart phone 106c, a photo camera 106d, a palmtop or handheld device 106e, or a tablet 106f. All this can be done without manual work. No network connectivity or additional cost is required.
- the present systems and methods relate to a data storage device for storing 2D color space encoded images, methods of encoding and decoding the 2D color space encoded images, and application of the 2D color space encoded images to data exchange.
- the present disclosure relates to encoding, transmission, and decoding of machine-based data using an appropriately formatted high capacity color image.
- the present systems and methods can be utilized, for example, for compact backup of printed materials, and/or data exchange between a color-image-displaying device and a plurality of image-reading devices.
- Figures 2A-2B illustrate the 2D color space encoded image 102 in accordance with certain embodiments of the present disclosure.
- encoded image 102 includes a number of rectangular cells 202 of different colors.
- encoded image 102 can include a black frame 204, a white frame 206, a "zebra frame" 208 having alternating colors, and color calibration cells 210.
- Figure 2B illustrates a close-up view of the black frame 204, the white frame 206, the zebra frame 208, and the color calibration cells 210 in accordance with certain
- Black frame 204 and white frame 206 can be used for rough localization of the data image including rectangular cells 202, determination of geometric distortion of the data image, and estimation of cell size and scale of rectangular cells 202.
- Zebra frame 208 can be used for further calibration of cell size for rectangular cells 202.
- Color calibration cells 210 can be used for determining a number of colors N c used for encoding the data, and for indexing the colors to map the colors to numbers for encoding and decoding.
- rectangular cells 202 can use more than eight different colors.
- the number of colors can be expressed as N c , for example N c > 8.
- the number of colors is selected to be a power of two.
- Figure 3 illustrates a method 300 that the system performs for encoding an image in accordance with certain embodiments of the present disclosure.
- color-difference metrics can help achieve stable color resolution for image-source media and image-reading devices.
- Most imaging devices operating in the visible spectrum are adapted to human eye color resolution.
- a color space describes color capabilities of a particular device by relating numbers to actual colors.
- Embodiments of the present disclosure utilize metrics based on low-cost non-Euclidean distance in red green blue (RGB) color space.
- RGB red green blue
- the present system uses color space metrics which are close to Commission International de l'eclairage (CIE) 1976 (L*,u*,v*) color space metrics.
- CIE Commission International de l'eclairage
- the CIELUV color space distributes colors roughly proportional to perceived color differences.
- the present systems and methods are able to use any color space, including the CIE 1931 XYZ color space, CIELAB color space, and CIEUVW color space.
- embodiments of the present system are based on the CIELUV color space, according to experimentation, the color space used in certain embodiments is advantageously less sensitive to a color temperature of relevant image displaying media or device, and advantageously less sensitive to external illumination. Assuming R, G, and B are one byte
- r describes an average red component value of C 1 and C 2 .
- the present system first receives machine data for encoding into an image.
- the machine data can be contained in a file.
- the present system compresses the file (step 302).
- the machine data can be compressed into a binary compressed file such as zip, rar, arc or any other archive format file.
- the present system determines an appropriate color encoding, illustrated by box 310. For example, the present system maps the resulting code sequence to a stream of integers from 0 to N c -1 , inclusive. Using the stream of integers, the present system creates a bitmap with frame formatting. Generation of frame formatting is described in further detail later. The present system fills the interior of the frames with color bitmap cells, encoded as described following.
- the encoding can use error correction.
- a non- limiting example of error correction is the two-stage error correction described herein.
- the encoding can use scrambling.
- the encoding can use error correction in combination with scrambling.
- the present system determines the color of each cell based on the color calibration cells. The resulting encoded image can then be sent to any display, including a color printer, display, or other color image output device.
- the present system then performs a first level of error correction (step 304).
- error correction is that the present system is able to decode an image properly, even if a portion of the image is damaged.
- the present system can determine a header containing a cyclic redundancy check (CRC) error- detecting code, file name, format information, and sequence number (e.g., if the machine data and resulting encoded image represent only part of a larger data stream such as a video stream).
- CRC cyclic redundancy check
- the present system can use any error detecting code such as repetition codes, addition of parity bits, checksums, hash functions, or more powerful error correcting codes.
- the present system can use a Reed-Solomon encoder of high order.
- a Reed-Solomon error correction code is a cyclic error-correcting code capable of detecting and correcting multiple errors in a bit stream.
- the present system can use other error-correcting codes such as low-density parity-check (LDPC) codes or turbo codes.
- LDPC low-density parity-check
- Reed-Solomon error correction codes are capable of detecting errors, erasures, and combinations thereof.
- a word size for this high order level of Reed-Solomon encoding can be equal to k*log 2 (N c ) rounded down, where k > 1.
- the two-stage error coding can perform high order Reed-Solomon encoding in a first stage, and low order Reed-Solomon encoding in a second stage.
- the second stage can also include smaller words.
- the word size can be equal to log 2 (N c ) bits, rounded down.
- the present system then scrambles the obtained code (step 306).
- the resulting code can be interleaved using a predefined pseudorandom sequence.
- the present system scrambles the obtained code to spread out potential errors.
- the two-level error correction described herein can perform better. That is, when registering or capturing an image for decoding, there can be color distorgions due to non-uniform lighting, or damage on the media on which the image is printed. For example, the media can have spots, be wrinkled, and the like.
- the scrambling provides that "bad" color cells with uncertain data can be distributed uniformly (i.e., independently) into different encoding blocks, thereby decreasing the number of errors per block. Because error correction can have upper limits of correctable errors, the present spreading improves the effectiveness of the error correction.
- the present system then performs a second level of error correction (step 308).
- the resulting scrambled code is encoded using a Reed- Solomon encoder with .
- the word size can be selected to be smaller than the word size used in the first level of error correction.
- this two-stage error correction allows the present system to mark unrecoverable blocks of data during a first stage as erasures.
- the error correction described herein finds an index location of an error word inside a block, and also corrects the error word to its correct or true value.
- the two-stage error correction allows the present system to correct twice as many erasures as errors, as described in more detail later.
- the present system is able to use any kind of high definition (HD) color registration device to register an encoded image.
- registration devices can include a digital camera, a smartphone camera, a tablet camera, a video camera, a webcam, a scanner (to scan a hard copy image), etc.
- Figure 4 illustrates a method 400 that the system performs for decoding an image in accordance with certain embodiments of the present disclosure.
- an encoded image can copy a registered image to any processing device containing a decoding module.
- An example processing device can include a computer, containing a decoding module with computer-readable instructions for decoding, where the computer-readable instructions are stored on a non- transitory computer storage medium, or containing hardware having hard-coded or embedded decoding instructions stored thereon.
- decoding method 400 includes two high-level processes: (1) image recognition, and (2) two-stage Reed-Solomon decoding.
- the present system uses Viterbi decoding as a Reed-Solomon decoder.
- the present system locates the main frame (step 402). For example, the present system can locate the black frame and the white frame vertices. The present system can further determine the middles of the corresponding edges of the black frame and the white frame. If the main frame is not found (step 404: No), the present system returns an error (step 406).
- the error can be that the image cannot be decoded, or the error can be more specific such as that the main frame cannot be found.
- the present system corrects geometric distortion based on the main frame and the zebra frame (step 412).
- Geometric distortion can occur when a user uses a camera lens, for example on a smartphone or tablet camera, or on a digital camera, to decode an image. Accounting for distortion is described in further detail later, in connection with Figure 6.
- the present system locates the color calibration cells (step 408).
- the color calibration cells are located inside the black frame and the white frame, on the left of the rectangular cells encoding the machine data.
- the color frame could be located outside the black frame, between the black and white frames, or in other locations within the white frame.
- the present system decodes the colors in the rectangular cells (step 410). In general, for every pixel found in the encoded image, the present system finds the closest sample pixel based on the color calibration cells and substitutes the sample pixel for the detected pixel. In some embodiments, the present system obtains a color-value correspondence. The present system determines cell size calibration based on the zebra frame. The present system divides the data image into color cells. When decoding the image, the present system captures or collects all colors belonging to a given pixel rectangle. If most of the pixel colors in the pixel rectangle could be recognized as one color from the color calibration cells, that color from the color calibration cells is used. Otherwise, the present system marks the pixel as an erasure.
- the present system treats the whole pixel block as an erasure.
- the present system reads the rectangular cells sequentially and determines an index of the nearest color from the color calibration cells to the median cell color. In particular, the present system determines the nearest color according to nearest Euclidean distance in the appropriate color space, according to Equation (1), described earlier.
- the present system decodes the bytes (step 414).
- the present system applies a corresponding decoder to the error-correcting encoder described earlier.
- the present system applies a low-level Reed-Solomon decoder to the code stream obtained from the decoded colors. Accordingly, due to the nature of the error- correcting code, the present system is able to restore erasures and errors in the code stream. If the present system detects unrepairable blocks, the unrepairable blocks are marked as "erasures.”
- the present system then descrambles the bytes (step 416). In some embodiments, the present system de-interleaves the resulting byte stream.
- the present system then decodes the original information based on the decoded byte stream (step 418).
- the present system uses a corresponding decoder to the error-correcting encoder described earlier, to restore pixel-block- level erasures and errors.
- the present system applies a high-level Reed-Solomon decoder. After applying the high-level Reed-Solomon decoder, if some pixel blocks remain un-repairable, the present system attempts to change the indices to those indices corresponding to the next nearest color in the color calibration cells, and then repeats Reed-Solomon decoding of the modified block. If error free data is obtained, the present system maps the resulting sequence of integers to a bit stream.
- the present system then parses the resulting bit stream and computes a cyclic redundancy check (CRC) of the data.
- CRC cyclic redundancy check
- the present system compares the resulting CRC with the CRC contained in the header of the image.
- the present system then saves or appends the file.
- the two-level error correction used in the present system and described earlier in connection with Figures 3 and 4 allows the present system to correct two types of errors: errors and erasures.
- the Reed-Solomon error-correction encoding used is able to detect errors (which correspond to wrong, incorrect, or unexpected
- correcting erasures can be performed twice as effectively than correcting errors.
- the present system uses a two-level error correction schema.
- N c 16 (i.e., 2 4 ). Accordingly, there are sixteen distinctive colors which allow an encoded image to encode 4 bits of information per rectangular cell. Every byte of information (8 bits) is encoded by two color indices.
- the group of half-bytes is then appended with Reed-Solomon source control data determined based on the group of half-bytes. Because the Reed-Solomon source control data can be about the same size as the input data, the addition of the Reed-Solomon source control data results in the size of the group reaching fifteen bytes. For example, the size of the input data and the control data block size can be fifteen bytes.
- Each half-byte in the group is mapped to an appropriate color, for example by using the corresponding half-bytes as indices into the color array. Accordingly, the encoding process applies two levels of Reed-Solomon encoding, first at the byte array level and second at the half-byte level.
- the present system collects all colors belonging to a detected pixel rectangle. If most of the colors in the pixel rectangle could be recognized as one of the colors in the color calibration cells, the present system uses the corresponding color in the color calibration cells. Otherwise, the pixel rectangle is marked as an erasure. If a pixel-level block cannot be decoded, the whole pixel block is treated as an erasure. As described earlier, the erasures can be further restored by an appropriate error-correction algorithm.
- the two-level error correction and leveraging of erasure determinations significantly improves the quality of the decoding described earlier in connection with Figure 4. In particular, the two-level error correction described herein allows the present system to recover information which otherwise would be lost.
- Figure 5 illustrates a block diagram of color calibration cells for restoration of proper color based on distinguishable color samples in accordance with certain embodiments of the present disclosure.
- Figure 5 includes color calibration cells 210.
- Color calibration cells 210 include all colors used to encode the rectangular cells.
- a white frame or border surrounds color calibration cells 210 for the color white.
- the present system may also include white as a color block in the color calibration cells arranged on the left hand side. The present system discerns each color based on its placement within color calibration cells 210.
- the present system then stores distorted pixels as color samples. Different variants of a distorted pixel are saved to point or refer to the same correct pixel. That is, distorted pixels are determined dynamically, based on the position of their colors among the color calibration cells. The distorted pixels are assigned estimated colors according to the color calibration cells.
- the present system translates a distorted pixel into one of the original colors in color calibration cells 210 using the nearest original color to the distorted pixel.
- color C (R, G, B) represent a red green blue (RGB) component representation of the color.
- RGB red green blue
- Equation (1) described earlier, a pseudo-Euclidean distance between two colors C; and C2 can be given by AC, as described in Equation (1):
- a color mapping can be represented by the set of pairs: (distorted color)— > (correct color).
- the distorted color can be Ci, and the correct color can be C2.
- the number of such color pairs should be greater than or equal to N c , the total number of colors. This mapping can be determined based on the color calibration cells and on the color arrangement therein.
- the present system iterates over all pairs of distorted colors and correct colors. In particular, the present system selects the pair in which the distorted color portion of the pair is closest to the correct or proper color c . In some embodiments, the determination of whether the distorted color portion is closest to the correct or proper color is made according to the pseudo-Euclidian metrics in the RGB color space. That is, the present system selects the pair in which AC is smallest according to Equation (1). The selected pair provides the correct color.
- the present system allows the correct colors to be restored, because the present system saves the correspondence between the distorted values and the original values.
- the present system is able to leverage information about the way in which the colors were distorted relative to the original values as captured in the color calibration cells.
- Frame arrangement for automatic image geometrical distortion correction is able to leverage information about the way in which the colors were distorted relative to the original values as captured in the color calibration cells.
- Figure 6 illustrates a block diagram of a frame arrangement for geometrical distortion correction of an encoded image in accordance with certain embodiments of the present disclosure.
- the present system includes arrangements to recognize placement of rectangular cells and other elements in the encoded image.
- these arrangements can include black frame 204, white frame 206, zebra frame 208, and color calibration sidebar 210 (shown in Figure 2).
- the black frame and white frame surround the encoded rectangular cells.
- the color calibration sidebar contains sample colors (described earlier, in connection with Figure 5).
- the zebra frame surrounds the encoded rectangular cells to allow the present system to determine appropriate resolution and pixel division of the encoded image.
- the black frame and white frame allow the present system to determine and correct nonlinear distortion.
- nonlinear distortion can be introduced, for example, by camera lenses when registering an encoded image for decoding.
- the present system uses the white frame as follows.
- the white frame can be restricted by curve x le ft(y) 602, curve x r ight(y) 604, curve yt op (x) 606, and curve ybottom(x) 608.
- the present system can determine parameters a and b (0 ⁇ a ⁇ l and 0 ⁇ b ⁇ l) according to the following equations:
- the equation described above maps the area restricted by curves 602-608 to a unit rectangle defined by 0 ⁇ a ⁇ l , 0 ⁇ b ⁇ l .
- the unit rectangle can represent what the image would look like when "straightened out,” by mapping the area restricted by curves 602-608 to the unit rectangle. That is, the distorted boundary of the image determined according to the area restricted by curves 602-608 can be mapped to the "straightened out" unit rectangle.
- the zebra frame can be used to determine parameters a and b.
- the present distortion correction therefore allows the original area having curved or non-linear sub-regions to be transformed according to the unit rectangle using parameters a and b.
- the zebra frame allows the present system to determine a resolution of the embedded picture, and to divide the image into "bold” or unknown pixels. As described earlier, the color value of some pixels may be unknown. "Bold" pixels allow the present system to determine the proper color value of a pixel according to a voting process. In some embodiments, the voting process can choose the color value of the most frequent pixel close to the "bold" or unknown pixel to be the color value of the "bold" pixel. Otherwise, if the result of the voting is unclear— for example, if there is no pixel with a frequency much larger than the other pixels— the present system can mark the pixel as an erasure (i.e., missing). Therefore, using the two-level error correction described earlier, the pixel can be restored.
- Image Fragmentation can choose the color value of the most frequent pixel close to the "bold" or unknown pixel to be the color value of the "bold" pixel. Otherwise, if the result of the voting is unclear— for example, if there is no
- Figure 7 illustrates a block diagram for frame fragmentation for distortion correction in accordance with certain embodiments of the present disclosure.
- the rectangular cells can be divided into sub-images 704 using separating lines 702.
- Frame fragmentation or image fragmentation refers to a complementary technique to distortion correction (shown in Figure 6).
- dividing the image into a set of sub-images 704 allows the present system to work with every sub-image 704, without requiring the distortion compensation technique described earlier because sub-images 704 are sufficiently small that there is not as much distortion as with the entire encoded image.
- sub-images 704 can be separated with separating lines 702.
- separating lines 702 can be black lines, which can also became part of the zebra border.
- the present system can use the same encoding and decoding techniques described earlier (shown in Figures 3 and 4) for encoding and decoding of sub-images 704.
- the present system can leverage the two-level error correction, scrambler, etc.
- the present system can skip the distortion correction described earlier (shown in Figure 6).
- the present system can leverage the relatively smaller size of sub-images 704 to skip non- linear distortion compensation of each sub-image 704. Accordingly, the present system can decode sub-images 704 with better accuracy.
- Figures 3 and 4 include processes that, in various embodiments, are carried out by a processor under the control of computer-readable and computer-executable instructions.
- Embodiments of the present disclosure may thus be stored as non-transitory computer- readable media or computer-executable instructions including, but not limited to, firmware updates, software update packages, or hardware (e.g., ROM).
- disabling refers to actions and processes of a computer system or similar electronic computing device or processor.
- the computer system or similar electronic computing device manipulates and transforms data represented as physical (electronic) quantities within the system memories, registers or other such information storage, transmission or display devices.
- the present systems and methods can be implemented in a variety of architectures and configurations.
- the present systems and methods can be implemented as part of a distributed computing environment, a cloud computing environment, a client server environment, etc.
- the embodiments described herein may be discussed in the general context of computer-executable instructions residing on some form of non-transitory computer-readable storage medium, such as program modules, executed by one or more computers, computing devices, or other devices.
- non-limiting examples of computer-readable storage media may include storage media and communication media.
- program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types.
- the functionality of the program modules may be combined or distributed as desired in various embodiments.
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