PiCode: a New Picture-Embedding 2D Barcode
ABSTRACT
Nowadays, 2D barcodes have been widely used as an interface to connect
potential customers and advertisement contents. However, the appearance of a
conventional 2D barcode pattern is often too obtrusive for integrating into an
aesthetically designed advertisement. Besides, no human readable information is
provided before the barcode is successfully decoded. This paper proposes a new
picture-embedding 2D barcode, called PiCode, which mitigates these two
limitations by equipping a scannable 2D barcode with a picturesque appearance.
PiCode is designed with careful considerations on both the perceptual quality of
the embedded image and the decoding robustness of the encoded message.
Comparisons with existing beautified 2D barcodes show that PiCode achieves one
of the best perceptual quality for the embedded image, and maintains a better
trade-off between image quality and decoding robustness in various application
conditions. PiCode has been implemented in Matlab on a PC and some key
building blocks have also been ported to Android and iOS platforms. Its
practicality for real-world applications have been successfully demonstrated.
EXISTING SYSTEM
The three squarish finder patterns are usually kept intact by the beautifying
process since they are pivotal in the QR code detection process. The obtrusive
appearance of such finder patterns pose a strong limitation on the achievable
perceptual quality of the embedded picture. Similarly, the timing and alignment
patterns in the interior region of the high capacity QR code severely affects the
perceptual quality. On the other hand, suppressing these patterns without taking a
sufficient remedial measure, as in QR Image , leads to degradation in the decoding
performance.
The modulation of the beautified QR codes using the second approach
introduces dark or bright dot-like patterns in the embedded images. However, to
achieve better perceptual quality by simply lowering the contrast or size of such
dot-like patterns increases the probability of demodulation .
PROPOSED SYSTEM
In this section, the proposed PiCode system is described with an emphasis
on the novel aspects of the encoding and decoding algorithms. For the encoding
part, the details of the modulation scheme will be presented to illustrate how
PiCode preserves the perceptual quality of the embedded image while minimizing
the interference of the latter incurred on the modulation waveform. For the
decoding part, the algorithms for performing corner detection, module alignment
and demodulation will be described.
Algorithm:
1.QR code Generating Algorithm
2.Bar Code Generator.
3.Embedding Algorithm.
Architecure:
MODULE DESCRIPTION
 New Picture-Embedding.
 QR Code.
 2D Barcode.
 Embedding Image System.
New Picture-Embedding
Appearance of a conventional 2D barcode pattern is often too obtrusive for
integrating into an aesthetically designed advertisement. Besides, no human
readable information is provided before the barcode is successfully decoded. This
paper proposes a new picture-embedding 2D barcode, called PiCode, which
mitigates these two limitations by equipping a scannable 2D barcode with a
picturesque appearance. PiCode is designed with careful considerations on both the
perceptual quality of the embedded image and the decoding robustness of the
encoded message. Comparisons with existing beautified 2D barcodes show that
PiCode achieves one of the best perceptual quality for the embedded image, and
maintains a better trade-off between image quality and decoding robustness in
various application conditions. PiCode has been implemented in Matlab on a PC
and some key building blocks have also been ported to Android and iOS platforms.
Its practicality for real-world applications have been successfully demonstrated.
QR CODE
QR code is an invention of Denso Wave Inc. and has been included in the
ISO standard.It was created for industrial applications, such as auto-identification
and tracking of electronic parts Its pattern is in black and white, and consists of
some large fixed patterns which are designed to guarantee detection and decoding
robustness. QR code contains three squarish finder patterns located at the top left,
top right and bottom left corners, respectively, an alternating black and white
timing pattern between adjacent finder patterns, as well as a smaller squarish
alignment pattern at the bottom right region For the high capacity there are more
fixed patterns located in the interior region of the barcode. Such fixed patterns are
only present in QR codes with a storage being greater than 196 bytes. This is
because as the barcode capacity increases, the module alignment accuracy becomes
more critical and the fixed patterns can be utilized to improve module alignment.
2D BARCODE
2D barcodes have been widely used as an interface to connect potential
customers and advertisement contents. However, the appearance of a conventional
2D barcode pattern is often too obtrusive for integrating into an aesthetically
designed advertisement. Besides, no human readable information is provided
before the barcode is successfully decoded. This paper proposes a new pictureembedding 2D barcode, called PiCode, which mitigates these two limitations by
equipping a scannable 2D barcode with a picturesque appearance. PiCode is
designed with careful considerations on both the perceptual quality of the
embedded image and the decoding robustness of the encoded message.
Comparisons with existing beautified 2D barcodes show that PiCode achieves one
of the best perceptual quality for the embedded image, and maintains a better
trade-off between image quality and decoding robustness in various application
conditions. PiCode has been implemented in Matlab on a PC and some key
building blocks have also been ported to Android and iOS platforms. Its
practicality for real-world applications have been successfully demonstrated.
Embedding Image System:
We now briefly outline the decoding procedure for QR code, which imposes
a decodability constraint for designing beautified QR codes. After the image of a
QR code is captured, it is binarized to a black and white image. Next, the detection
algorithm is applied to the binarized image to locate the three squarish finder
patterns. The detection is conducted by searching for the black-white-black-whiteblack pattern with both the horizontal and vertical directions. The alignment
pattern is also located in a similar way. The detected barcode region is then
verified against some acceptance criteria, including i) the estimated module
dimensions (i.e. length and width) should only vary within a predefined range; ii)
the respective numbers of modules in the horizontal and vertical dimensions should
be almost the same; and iii) the positions of the four squarish finder/alighment
patterns should be nearly rectangular in shape in the barcode image. Based on the
four detected patterns, an appropriate perspective transform, which compensates
for the perspective distortion incurred in the image capturing process, is found and
is applied to convert the detected barcode region into a square region. The position
of each module is then found with reference to the alternating black and white
timing patterns. Within each binarized module, the central pixel is used to
demodulate the data bit as depending whether it is black or white. After
demodulation, a sequence of bits are obtained. Finally, the message is recovered by
reorganizing the bits according to the header information and performing the
corresponding Reed-Solomon code decoding.
SYSTEM SPECIFICATION
Hardware Requirements:
• System
: Pentium IV 2.4 GHz.
• Hard Disk
: 40 GB.
• Floppy Drive
: 1.44 Mb.
• Monitor
: 14’ Colour Monitor.
• Mouse
: Optical Mouse.
• Ram
: 512 Mb.
Software Requirements:
• Operating system : Windows 7 Ultimate.
• Coding Language
: ASP.Net with C#
• Front-End
: Visual Studio 2010 Professional.
• Data Base
: SQL Server 2008.
CONCLUSION
This paper has designed a novel picturesque 2D barcode, named the PiCode.
Comparing with existing beautified QR codes, it provides one of the best
perceptual quality in preserving the aesthetic appearance of the embedded image,
while maintains the decoding robustness. It is achieved by the design of barcode
pattern and better decoding algorithms. The PiCode is designed with less obtrusive
fixed patterns to avoid distortions on the embedded image, and a modulation
scheme which represents the data bit value adaptively with the embedded image
intensity. On the other hand, some key steps of the decoding process have also
been developed to guarantee the decoding robustness including the coarse-fine
corner detection, module alignment with barcode structural information and
demodulation with information from all pixels in each module. Comparisons with
the existing beautified QR codes by experimental results show that PiCode has
maintained a better trade-off between the perceptual quality and the decoding
robustness (or normalized data capacity). To evaluate its practicality, the PiCode
system has been implemented in Matlab on a PC, and as mobile application
softwares in Android and iOS platforms. The perceptual quality and the decoding
robustness of the PiCode system have been successfully demonstrated. In the
future, the unobtrusive pilot symbols will be embedded into the PiCode center to
serve as center alignment pattern and training symbols for the camera response
function. Hopefully, a lower BEP in the demodulation process can be achieved.