Barcode Image Research Articles

Two-Dimensional Barcode Encryption Technology Based on Improved Chaotic Sequences of Logistics

A new method for two-dimensional barcode encryption through using improved chaotic sequences of logistics has been proposed. The image of two-dimensional barcode was divided into two parts and chaotic sequence for encryption with the two parts was used respectively. Experiments results denoted that five key ensured the encrypted image higher security. The MSE between the original image and the encrypted image is 3.49×106. Computer simulations are presented to verify its good resistance to salt and pepper noise.

UCloud: a user‐centric key management scheme for cloud data protection

One of the most challenging problems of cloud service solicitation is to persuade users to trust the security of cloud service and upload their sensitive data. Although cloud service providers can claim that their services are well-protected by elaborate encryption mechanisms, traditional cloud systems still cannot persuade the users that even if the cloud servers are compromised, the data are still securely protected. This study proposes uCloud, a user-centric key management scheme for cloud data protection, to solve this problem. uCloud utilises RSA and indirectly encrypts users' data by users' public keys, but stores the users' private keys on neither servers nor users' PCs; instead, the private keys are stored on users' mobile devices and presented via two-dimensional (2D) barcode images when they are utilised to decrypt users' sensitive data. In this manner, users' data are safely protected even if the cloud servers are compromised. Also, uCloud provides users with the experience of managing visible private keys by storing the keys into mobile phones and displaying them via 2D barcodes. Moreover, three scenarios: personal storage, home surveillance and enterprise storage scenarios are proposed to present the practicability of uCloud. In addition, a hierarchical structure is designed for basic key backup and data sharing in the proposed scheme.

Designing and Implementation of 2D Character Barcode

Base on 2D barcode DM and QR, a new2D character barcode, is proposed in this paper. It is different with the traditional 2D barcode. It is a character matrix instead of the image barcode. The encoding rules, decoding rules and symbol structure of this character barcode are designed and implemented. Then the error-correcting code is studied and added into the encoded information. Finally the 2D character barcode is verified on PC. The experiments show that the 2D character barcode has very small capacity and can be transmitted as the character message among the mobile terminals. It can well overcome high loss rate when the image of 2D barcode is transmitted as a multimedia message and avoid the problem that some mobile terminals can not support the multimedia messages.

Digital image watermarking spread-space spread-spectrum technique based on Double Random Phase Encoding

In this paper a digital invisible image watermarking technique is proposed based on a numerical simulation of optical Double Random Phase Encoding (DRPE). This technique utilizes the capability of the DRPE to reversibly spread the energy of the input information in both the space and the spatial frequency domains using two diffusers. The watermark is in the form of a digital barcode image which is numerically encrypted using a simulation of the optical DRPE process. This produces a random complex image, which is then processed to form a real valued random image with a low number of quantization levels. This signal is added to the host image. Extraction of the barcode involves applying an inverse DRPE process to the watermarked image followed by a low pass filter. The various noise terms due to the decryption procedure are investigated and we show that these noise terms share the same first-order statistical properties as optical speckle. The results presented indicate the feasibility and robustness of the proposed method and it is demonstrated that even when using very few quantization levels, i.e. 2-level, the watermark can still be extracted with very small errors.

Barcode Server: A Visualization-Based Genome Analysis System

We have previously developed a computational method for representing a genome as a barcode image, which makes various genomic features visually apparent. We have demonstrated that this visual capability has made some challenging genome analysis problems relatively easy to solve. We have applied this capability to a number of challenging problems, including (a) identification of horizontally transferred genes, (b) identification of genomic islands with special properties and (c) binning of metagenomic sequences, and achieved highly encouraging results. These application results inspired us to develop this barcode-based genome analysis server for public service, which supports the following capabilities: (a) calculation of the k-mer based barcode image for a provided DNA sequence; (b) detection of sequence fragments in a given genome with distinct barcodes from those of the majority of the genome, (c) clustering of provided DNA sequences into groups having similar barcodes; and (d) homology-based search using Blast against a genome database for any selected genomic regions deemed to have interesting barcodes. The barcode server provides a job management capability, allowing processing of a large number of analysis jobs for barcode-based comparative genome analyses. The barcode server is accessible at http://csbl1.bmb.uga.edu/Barcode.

A two-stage quality measure for mobile phone captured 2D barcode images

2D barcodes are widely used in many commercial applications where a scanning device is normally used to capture them. When mobile phones are used to capture 2D barcodes, the obtained images are usually distorted due to cheap camera lens and sensors, handshake and poor lighting conditions. These badly distorted images require a long decoding process which results in an error message generated or wrongly decoded information. In this paper, we propose a two-stage quality measure for the mobile phone captured 2D barcodes in order to reject those poor quality images. The proposed method is based on the global bimodal distribution features and the local finder pattern detection. Experimental results on QR code images show that the proposed two-stage quality measure has 97.64% prediction accuracy with an average run time of 110ms by rejecting distorted undecodable barcode images in advance. The proposed method also has good generalizability to “unseen” camera models and performs well under different lighting conditions. Experiments on data matrix images show that our quality measure can be extended to 2D barcode patterns with similar features.

Research of EAN-13 Barcode Identification Based on Unitary Decimalization

This paper has put forward a decimal system based on binary system for representing figures of barcode image. Different with traditional distance of similar line unitary method, this paper invents the unitary decimalize method for EAN-13 image identification. Counting and sorting the times of the number that appears when scan the image to calculate the width of unit bar not use the averaging method, which has the same identification effect but more simple and effective. At last make the corresponding program to verify the method, the result shows this method performs well. It is not only suitable to the horizontal positive-going or reversed-going barcode image but also to the oblique barcode image.

Grating-dot two-dimensional barcode patterns with extra binary data for encoding secret information

The usual two-dimensional (2D) barcode patterns do not encrypt secret information. However, secret information is sometimes needed to increase the security features of barcode patterns. Therefore, this paper proposes 2D barcode patterns created by two-beam writers to encrypt extra binary data for encoding secret information. The proposed 2D barcode patterns are composed of many grating dots and the fringes of the grating dots are classified into four types. The first type of fringe possesses a pitch of 1.1 μm and an orientation of −45°, the second type of fringe possesses a pitch of 1.2 μm and an orientation of −45°, the third type of fringe possesses a pitch of 1.1 μm and an orientation of 45°and the fourth type of fringe possesses a pitch of 1.2 μm and an orientation of 45°. All the fringes with a 1.1 μm pitch can show a color and all the fringes with a 1.2 μm pitch can show another color when a microscope is used to inspect them. Therefore, extra binary data for encoding secret information can be formed with the two pitches. On the other hand, all the fringes with a −45° orientation can become bright for a viewing direction and all the fringes with a 45° orientation can become bright for another viewing direction when one looks at them. Therefore, the grating dots with the −45° fringe orientation and the grating dots with the 45° fringe orientation can be used to show a positive barcode image and a negative barcode image, respectively. Both the positive and negative barcode images can be used to derive the barcode data. The experiment shows that the proposed barcode patterns can be used conveniently and correctly.

Morphological segmentation of 2-D barcode gray scale image

Segmentation is a key process of 2-D barcode identification. In this paper we propose two 2-D barcode image segmentation algorithms under complex background. The first algorithm is an expansion of multi-scale morphology reconstruction and it can acquire a good segmentation result. However, this algorithm is not suitable for fast real-time image processing due to large computation. To fix the shortcoming of the first algorithm we put forward a fast real-time image segmentation algorithm. The proposed approach is applied in experiments on 2D barcodes with complicated background. In experiments, the second proposed method can maintain image segmentation accuracy while significantly reducing the time consumption.

Predicting a novel pathogenicity island inHelicobacter pyloriby genomic barcoding

To apply a new, integrated technique for visualizing bacterial genomes to identify novel pathogenicity islands in Helicobacter pylori (H. pylori). A genomic barcode imaging method (converting frequency matrices to grey-scale levels) was designed to visually distinguish origin-specific genomic regions in H. pylori. The complete genome sequences of the six H. pylori strains published in the National Center for Biotechnological Information prokaryotic genome database were scanned, and compared to the genome barcodes of Escherichia coli (E. coli) O157:H7 strain EDL933 and a random nucleotide sequence. The following criteria were applied to identify potential pathogenicity islands (PAIs): (1) barcode distance distinct from that of the general background; (2) length greater than 10000 continuous base pairs; and (3) containing genes with known virulence-related functions (as determined by PfamScan and Blast2GO). Comparison of the barcode images generated for the 26695, HPAG1, J99, Shi470, G27 and P12 H. pylori genomes with those for the E. coli and random sequence controls revealed that H. pylori genomes contained fewer anomalous regions. Among the H. pylori-specific continuous anomalous regions (longer than 20 kbp in each strain's genome), two fit the criteria for identifying candidate PAIs. The bioinformatic-based functional analyses revealed that one of the two anomalous regions was the known pathogenicity island cag-PAI, this finding also served as proof-of-principle for the utility of the genomic barcoding approach for identifying PAIs, and characterized the other as a novel PAI, which was designated as tfs3-PAI. Furthermore, the cag-PAI and tfs3-PAI harbored genes encoding type IV secretion system proteins and were predicted to have potential for functional synergy. Genomic barcode imaging represents an effective bioinformatic-based approach for scanning bacterial genomes, such as H. pylori, to identify candidate PAIs.

2D Barcode Image Decoding

Barcode technology is one of the most important parts of Automatic Identification and Data Capture (AIDC). Quick Response code (QR code) is one of the most popular types of two-dimensional barcodes. How to decode various QR code images efficiently and accurately is a challenge. In this paper, we revise the traditional decoding procedure by proposing a serial of carefully designed preprocessing methods. The decoding procedure consists of image binarization, QR code extraction, perspective transformation and resampling, and error correction. By these steps, we can recognize different types of QR code images. The experiment results show that our method has better accuracy than Google open-source 1D/2D barcode image processing library Zxing-2.1. Moreover, we evaluate the execution time for different-size images. Our method can decode these images in real time.

이중 문턱 값과 적분영상을 이용한 2차원 바코드 영상의 적응적 이진화

본 논문에서는 2차원 바코드 영상을 위한 적응적 이진화 방법을 제안한다. 적응형 이진화 방법은 조명의 영향을 최소화하여 이진화를 수행하는 기술이다. 적응적 이진화 방법은 주로 문서 영상에 맞게 발전되어 왔다. 기존 방법들은 적응적 이진화에서 사용되는 박스에 대한 크기 설정 문제를 가지고 있다. 이 문제로 기존 방법들은 이차원 바코드 영상 인식에 적용하기에 부적절하다. 문제점을 극복하기 위해 먼저 박스크기와 기존 방법들의 문제점을 분석하고, 이를 기반으로 적분영상을 사용한 새로운 적응형 이진화 방법을 소개한다. 제안한 방법의 성능 입증을 위해 기존의 방법과 속도, 성능 비교 실험을 수행하였고 실험 결과는 기존 방법보다 우수함을 입증하였다. In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods that minimize light effects convert an original image into a binary image. The methods are applied to document image binarization. The methods, however, have problems of determining box size used in adaptive thresholding. thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we analysis the problem and propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing methods in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

Two-dimensional bar code out-of-focus deblurring via the Increment Constrained Least Squares filter

When a two-dimensional bar code is away from a camera’s focus, the image is blurred by the convolution of the point spread function. In the presence of noise, the out-of-focus deblurring is an ill-posed problem. The two-dimensional bar code image has a very special form, making deblurring feasible. This paper proposes a fast deblurring algorithm called the Increment Constrained Least Squares filter that is specifically designed for two-dimensional bar code images. After analyzing the bar code image, the standard deviation of the Gaussian blur kernel is obtained. Then, the bar code image is restored through on iterative computations. In each iteration, the bi-level constraint of the bar code image is efficiently incorporated. Experimental results show that our algorithm can obtain better bar code image quality compared with existing methods. Our method can also improve the reading depth of field, which is an important performance parameter for bar code readers.

A VLSI Design of Image Rotation for Real Time 2-D Barcode Identification

Image rotation is a necessity for 2-D barcode identification. The computation complexity of image rotation is considered as a key problem of the implementation of real time 2-D barcode identification. This paper presents a novel VLSI structure for image rotation which can calculate the tilt angle of 2-D barcode image and rotate image to the horizontal way. The circuit to calculate the tilt angel of 2-D barcode is simple and effective and can be implemented with low hardware complexity. Image rotation algorithm takes use of improved CORDIC algorithm and Bi-linear interpolation and is implemented by high-speed pipelined architecture. The proposed architecture is implemented on the Altera Stratix IV FPGA. Experimental results show that the proposed architecture can rotate 2-D barcode images with arbitrary tilt angles to the horizontal way at 132MHz. Moreover, it can keep image details clear thus improving 2-D barcode identification rate.

Applications of Barcode Images by Enhancing the Two-Dimensional Recognition Rate

The paper not only proposed the latest Two- Dimensional Barcodes Image-processing Module, but also captured the smallest camera screens (320 240) with different focal distances and tried to find out ―Finder Pattern‖ for positioning images. Further, use CROBU (Conversion Ratio of Basic Unit) the thesis proposed to convert 2-D barcodes into 1-pixel ratio to match images before judging recognition rate of 2-D barcodes through matching. Normally speaking, 2-D barcodes are deciphered and recognized by software while the thesis recognizes 2-D barcodes and enhances implementation speed up to 10-cm accurate max. using image matching. The 2-D barcodes image-processing module the thesis proposed does capture and standardize image with complicated background or raw edge, which enhances 2- D barcodes recognition rate. The main point of this study is to construct a platform to manage or suggest nutrients human body needs. The Quick Response Code image of 2-D barcodes represents vitamin and calories information. 2-D barcodes taken instantly by MATLAB and CCD camera can be used to list nutrients from foods you eat recently and suggest what else you should eat for the purpose of health management.

Research on Recognition of the Two-Dimensional Barcode

Based on barcode PDF417 image’s characteristics, in order to improve the recognition of bar code, and reduce the bit error ratio, we proposed two methods. One way is to separate the calculation of the width of barcode’s unit from the extract codeword, another is the Recognition of bar blank sequence by using projection algorithm. Thereby, both methods reduce the impact of blurred images made by noisy pollution; the test proved that these two methods can deal with contaminated barcode image effectively.

Research on Cylinder Data Matrix Barcode Recognition

For the special requirements of recognition the Data Matrix barcode which marked on the cutter cylinder, considering of traditional recognition methods can’t solve the problems such as highlight reflection, cylinder distortion, the information incomplete collection, etc., causing low recognition rate. This paper presents a cutter cylinder Data Matrix barcode recognition method based on the sequence images mosaic and fusion. This method through rotating the cutter which is put in the auxiliary device to collect a group of cutter cylinder Data Matrix barcode sequence images, and then corrects the barcode longitudinal displacement to achieve calculating matching degree and image registration based on phase correlation method. At last, in order to ensure the structure of the barcode right, the sequence images are fused into three parts on the basis of the matching degree, and then achieve module division and distortion correction of each part. Finally according to the barcode module relation, three parts are fused into a barcode image which has a correct structure, and recognize the barcode image. The experimental results show that this method can solve the problem of recognition the cutter cylinder Data Matrix barcode, the decoding accuracy achieve 95%, and mosaic the time is less than 200ms.

Identification and Typing of Human Enterovirus: A Genomic Barcode Approach

Identification and typing of human enterovirus (HEVs) are important to pathogen detection and therapy. Previous phylogeny-based typing methods are mainly based on multiple sequence alignments of specific genes in the HEVs, but the results are not stable with respect to different choices of genes. Here we report a novel method for identification and typing of HEVs based on information derived from their whole genomes. Specifically, we calculate the k-mer based barcode image for each genome, HEV or other human viruses, for a fixed k, 1<k<7, where a genome barcode is defined in terms of the k-mer frequency distribution across the whole genome for all combinations of k-mers. A phylogenetic tree is constructed using a barcode-based distance and a neighbor-joining method among a set of 443 representative non-HEV human viruses and 395 HEV sequences. The tree shows a clear separation of the HEV viruses from all the non-HEV viruses with 100% accuracy and a separation of the HEVs into four distinct clads with 93.4% consistency with a multiple sequence alignment-based phylogeny. Our detailed analyses of the HEVs having different typing results by the two methods indicate that our results are in better agreement with known information about the HEVs.

A Skew Detection Algorithm for PDF417 Based on Feature Point

The automatic identification of 2D (two dimensional) bar code PDF417 is very sensitive to skew angle, but, the common skew angle detection methods have shortcomings such as weak performance in time complexity. In this paper, based on the properties of PDF417 character code and the extraction of feature points, we get skew angle of PDF417 bar code image using the least square method. Experiments show that this algorithm has virtue of less computation and high accuracy.

Precision Calculation Algorithm and Error Analysis of Zoom Magnification Measurement

The high precise measurement for magnification of optical system of microscope has been demonstrated by using special barcode design and precise barcode image processing technologies. The magnification measurement with 50ppm accuracy is obtained. According to the measurement error estimation, the accuracy for system magnification device is about 0.06%. Barcode position is possible to reach 0.5μm for low magnification and 0.1μm for high magnification.